Publications

• Rounding-Off Errors in Matrix Processes
• Can automatic calculating machines be said to think?
• Computability and λ-definability
• Digital computers applied to games
• Can a machine think?
• The Chemical Basis of Morphogenesis
• Systems of Logic Based on Ordinals
• Computable Numbers, with an Application to the Entscheidungsproblem
• Intelligent Machinery
• Some Calculations of the Riemann Zeta-Function
• Lecture to the London Mathematical Society on 20 February 1947
• Computing Machinery and Intelligence

Publications

• Proof of the Quasi-Ergodic Hypothesis
• On infinite direct products
• Continuous Geometry
• First Draft of a Report on the EDVAC
• Functional Operators: Measures and integrals
• Distribution of the Ratio of the Mean Square Successive Difference to the Variance
• Numerical Inverting of Matrices of High Order
• Numerical Integration of the Barotropic Vorticity Equation
• The General and Logical Theory of Automata
• Various Techniques Used in Connection With Random Digits
• Planning and Coding of Problems for an Electronic Computing Instrument
• On Rings of Operators II
• On an algebraic generalization of the quantum mechanical formalism (Part 1)
• The Computer and the Brain
• The Logic of Quantum Mechanics
• Theory of Games and Economic Behavior
• Theory of Self-Reproducing Automata
• Probabilistic logics and synthesis of reliable organisms from unreliable components
• A Model of General Economic Equilibrium
• Can We Survive Technology?
• On Complete Topological Spaces
• Fourier Integrals and Metric Geometry
• The Statistics of the Gravitational Field Arising from a Random Distribution of Stars
• Statistical Methods in Neutron Diffusion
• Physical Applications of the Ergodic Hypothesis
• On Regular Rings

Publications

• Generality in Artificial Intelligence
• From here to human-level AI
• Notes on formalizing context
• Epistemological Problems of Artificial Intelligence
• In Memoriam: Arthur Samuel: Pioneer in Machine Learning
• Programs with Common Sense
• An architecture of diversity for commonsense reasoning
• Making Robots Conscious of their Mental States
• What has AI in Common with Philosophy?
• Report on the Algorithmic Language ALGOL 60
• Applications of Circumscription to Formalizing Common Sense Knowledge
• Ascribing Mental Qualities to Machines
• Circumscription — A Form of Non-Monotonic Reasoning
• Revised Report on the Algorithmic Language Algol 60
• The Common Business Communication Language
• The well-designed child
• Correctness of a Compiler for Arithmetic Expressions
• First Order Theories of Individual Concepts and Propositions
• Queue- based Multi-processing Lisp
• Phenomenal Data Mining: From Data to Phenomena
• Chess as the Drosophila of AI
• Elaboration Tolerance
• Elephant 2000: A Programming Language Based on Speech Acts
• Formalizing Context (Expanded Notes)
• The Inversion of Functions Defined by Turing Machines
• Review of "Artificial Intelligence: A General Survey"
• LISP 1.5 Programmer's Manual
• History of Lisp
• LISP I Programmer's Manual
• A Basis for a Mathematical Theory of Computation
• Recursive Functions of Symbolic Expressions Their Computation by Machine, I
• Some Philosophical Problems from the Standpoint of Artificial Intelligence
• Modality, Si! Modal Logic, No!
• Formalization of two Puzzles Involving Knowledge
• REVIEW OF THE EMPEROR'S NEW MIND by Roger Penrose
• Actions and other events in situation calculus
• Some expert systems need common sense
• A Tough Nut for Proof Procedures
• Towards a Mathematical Science of Computation
• What is artificial intelligence?
• Artificial Intelligence, Logic and Formalizing Common Sense
• The Mutilated Checkerboard in Set Theory
• Coloring Maps And The Kowalski Doctrine
• Useful Counterfactuals
• Creative solutions to problems
• Free Will - Even for Robots
• Simple Deterministic Free Will
• The Little Thoughts of Thinking Machines
• A Logical AI Approach to Context
• Combining Narratives
• Parameterizing Models of Propositional Calculus Formulas
• Philosophical and Scientific Presuppositions of Logical AI
• Roofs And Boxes
• Notes On Self-awareness
• Appearance And Reality
• John Searle's Chinese Room Argument
• Networks Considered Harmful - For Electronic Mail
• Universality: Or Why There Are Separate Sciences
• An Everywhere Continuous Nowhere Differential Function
• Todd Moody's Zombies
• The Philosophy of AI and the AI of Philosophy
• ALGOL 48 and ALGOL 50: ALGOLic Languages in Mathematics
• Approximate Objects And Approximate Theories
• AI Needs more Emphasis on Basic Research
• What is common sense
• Concepts of Logical AI
• In the Betan Embassy on Barrayar
• Making Computer Chess Scientific
• An Example for Natural Language Understanding and the AI Problems it Raises
• The Future Of Scientific Publication
• The Robot and the Baby
• Some Sitcalc Formulas for Robot Soccer
• Children's To Save Defends Alfalfa Sprouts
• Teller, Heisenberg And The Bomb
• Letter To Christian Physicists
• "Computer chess" and human chess
• Formalization of Strips in Situation Calculus
• Teleservice
• What AI Needs From Computational Linguistics

Publications

• Expert Systems: Principles and Practice
• An Interview with EDWARD FEIGENBAUM
• The Handbook of Artificial Intelligence Volume III
• Computers and Thought
• Signal-to-Symbol Transformation: HASP/SIAP Case Study
• Soviet cybernetics and computer sciences, 1960
• An Information Processing Theory of Verbal Learning
• A Theory of the Serial Position Effect
• The Handbook of Artificial Intelligence Volume I
• The Handbook of Artificial Intelligence Volume II

Publications

• OM: "One Tool for Many (Indian) Languages"
• The Hearsay Speech Understanding System: An Example of the Recognition Process
• Transmembrane helix prediction using amino acid property features and latent semantic analysis
• Digital Information Organization in Japan
• Collaborative Research: ITR/ANIR: 100 Mb/sec For 100 Million Households
• Three Open Problems in AI
• A 3D-Object Reconstruction System Integrating Range-Image Processing and Rapid Prototyping
• Foundations and Grand Challenges of Artificial Intelligence
• Multiplicative Speedup of Systems
• Characterization of protein secondary structure
• Minimizing Computational Cost for Dynamic Programming Algorithms
• Comparative n-gram analysis of whole-genome protein sequences
• Computational Biology and Language
• An Integral Approach to Free-Form Object Modeling
• Knowledge Guided Learning of Structural Descriptions
• Spoken-Language Research at Carnegie Mellon
• The Digital Library of India Project: Process, Policies and Architecture
• Robotics and Intelligent Systems in Support of Society
• Improving Recognition Accuracy on CVSD Speech under Mismatched Conditions
• Interviews: The Challenges of Emerging Economies
• Computer vision: the challenge of imperfect inputs
• An overview of the SPHINX speech recognition system
• Techniques for the Creation and Exploration of Digital Video Libraries
• A Historical Perspective of Speech Recognition
• PCtvt: a Multifunction Information Appliance for Illiterate People
• Improving Pronunciation Inference using N-Best List, Acoustics and Orthography
• To Dream The Possible Dream
• A. M. Turing Award Oral History Interview with Raj Reddy
• Principal Component Analysis with Missing Data and Its Application to Polyhedral Object Modeling

Publications

• Structuring Causal Tree Models with Continuous Variables
• Distinctive properties of quantized vortices in superconducting films
• Invited Commentary: Understanding Bias Amplification
• The Mystery of Problem Representations
• A New Graphical Model for the Representation of Marginalized DAG-Representable Relations
• Vortexes are creating a stir in the superconductor field
• A Framework for Processing Value Judgments
• On the Connection Between the Complexity and Credibility of Inferred Models
• SCOUT: A Simple Game-Searching Algorithm with Proven Optimal Properties
• Asymptotic Properties of Minimax Trees and Game-Searching Procedures
• Storage Space versus Validity of Answers in Probabilistic Question-Answering Systems
• Probabilistic Analysis of the Complexity of A*
• A Space-Efficient On-Line Method of Computing Quantile Estimates
• A Computational Model for Causal and Diagnostic Reasoning in Inference Systems
• Causal and Diagnostic Inferences: A Comparison of Validity
• The Optimality of A* Revisited
• GODDESS: a Goal-Directed Decision Structuring System
• Reverend Bayes on Inference Engines: A Distributed Hierarchical Approach
• Fusion, Propagation, and Structuring in Belief Networks
• Bayesian Networks: a Model of Self-Activated Memory for Evidential Reasoning
• A Constraint-Propagation Approach to Probabilistic Reasoning
• How to Do with Probabilities What People Say You Can't
• On Evidential Reasoning in a Hierarchy of Hypotheses
• GRAPHOIDS: a Graph-Based Logic for Reasoning about Relevance Relations (Long Technical Report)
• GRAPHOIDS: a Graph-Based Logic for Reasoning about Relevance Relations (Technical Report)
• On the Logic of Representing Dependencies by Graphs
• Comprehension-Driven Generation of Meta-Technical Utterances in Math Tutoring
• Learning Link-Probabilities in Causal Trees
• Distributed Revision of Composite Beliefs
• Causal Networks: Semantics and Expressiveness
• A Distributed Diagnosis of Systems with Multiple Faults
• Evidential Reasoning Using Stochastic Simulation of Causal Models
• Embracing Causality Default Reasoning
• An Improved Constraint-Propagation Algorithm for Diagnosis
• Search Techniques
• Decomposing a Relation into a Tree of Binary Relations
• Enhancement Schemes for Constraint Processing: Backjumping, Learning, and Cutset Decomposition
• The Logic of Representing Dependencies by Directed Graphs
• Removing Redundancies in Constraint Networks
• Do we Need Higher-Order Probabilities and, If so, What do they Mean?
• On logic and probability
• On Probability Intervals
• Reasoning Under Uncertainty
• Evidential Reasoning Under Uncertainty
• The Logic of Influence Diagrams
• Conditional independence and its representations
• Axioms and Algorithms for Inferences Involving Probabilistic Independence
• Experimental Evaluation of Preprocessing Algorithms for Constraint Satisfaction Problems (Technical Report)
• Experimental Evaluation of Preprocessing Algorithms for Constraint Satisfaction Problems (Long Technical Report)
• Deciding Consistency of Databases Containing Defeasible and Strict Information
• On the consistency of defeasible databases
• Logical and algorithmic properties of independence and their application to Bayesian networks
• Locality-Bounded Rationality
• Probabilistic Semantics for Nonmonotonic Reasoning
• Probabilistic Semantics for Nonmonotonic Reasoning: A Survey
• d-Separation: From Theorems to Algorithms
• System Z: A Natural Ordering of Defaults with Tractable Applications to Nonmonotonic Reasoning
• Learning Structure from Data: A Survey
• From local to global consistency
• Reasoning with Belief Functions: An Analysis of Compatibility
• Rejoinder to Comments on "Reasoning With Belief Functions: An Analysis of Compatibility"
• Structure-driven algorithms for truth maintenance
• Graphoids: A Qualitative Framework for Probabilistic Inference
• A Maximum Entropy Approach to Nonmonotonic Reasoning
• Probabilistic and Qualitative Abduction
• Tree Decomposition with Applications to Constraint Processing
• On the Expressiveness of Networks with Hidden Variables
• Learning Causal Trees from Dependence Information
• Equivalence and Synthesis of Causal Models
• Faster Constraint Satisfaction Algorithms for Temporal Reasoning
• Directed Constraint Networks: A Relational Framework for Causal Modeling
• A Statistical Semantics for Causation
• A Theory of Inferred Causation
• Qualitative probabilities for default reasoning, belief revision, and causal modeling
• Structure identification in relational data
• Belief networks revisited
• An Algorithm for Deciding if a Set of Observed Independencies has a Causal Explanation
• Rank-based systems: A simple approach to belief revision, belief update, and reasoning about evidence and actions
• When Can Association Graphs Admit A Causal Explanation?
• A simple algorithm to construct a consistent extension of a partially oriented graph
• Qualitative Probabilities: A Normative Framework for Commonsense Reasoning
• Graphical Aspects of Causal Models
• A Calculus of Pragmatic Obligation
• Aspects of Graphical Models Connected With Causality
• From Bayesian Networks to Causal Networks
• Comment: Graphical Models, Causality, and Intervention
• A New Characterization of Graphs Based on Interception Relations
• Nonparametric Bounds on Causal Effects from Partial Compliance Data
• Universal Formulas for Treatment Effects from Noncompliance Data
• Bounds on Treatment Effects from Studies with Imperfect Compliance
• On the Statistical Interpretation of Structural Equations
• On the Logic of Iterated Belief Revision
• Causal Inference from Indirect Experiments (Long Technical Report)
• Causal Inference from Indirect Experiments (Technical Report)
• Symbolic Causal Networks for Reasoning about Actions and Plans
• On the Identification of Nonparametric Structural Models
• Mediating instrumental variables
• A Note on Testing Exogeneity of Instrumental Variables
• On the Testability of Causal Models with Latent and Instrumental Variables
• A Probabilistic Calculus of Actions
• Probabilistic Evaluation of Counterfactual Queries
• Counterfactual Probabilities: Computational Methods,Bounds, and Applications
• Qualitative Decision Theory
• On testing whether an Embedded Bayesian Network represents a probability model
• Bayesian Networks
• Three Statistical Puzzles
• Causal diagrams for empirical research (with Discussions)
• Causal diagrams for empirical research (with appendix on structural equations and counterfactuals)
• Probabilistic Evaluation of Sequential Plans from Causal Models with Hidden Variables
• Causation, action, and counterfactuals (Technical Report)
• Causation, action, and counterfactuals
• Testing Identifiability of Causal Effects
• Counterfactuals and Policy Analysis in Structural Models
• Graphical Models for Probabilistic and Causal Reasoning
• Structural and Probabilistic Causality
• Covariate Selection: A Simple Solution To a Long-Standing Problem
• Axioms of causal relevance (Long Technical Report)
• Axioms of causal relevance (Technical Report)
• A clinician's tool for analyzing non-compliance
• Identifying Independencies in Causal Graphs with Feedback
• TETRAD and SEM
• On the Foundation of Structural Equation Models or When Can We Give Causal Interpretation to Structural Coefficients?
• Bayesian Networks
• The Art and Science of Cause and Effect
• The New Challenge: From a Century of Statistics to the Age of Causation
• An Axiomatic Characterization of Causal Counterfactuals
• Causal Diagrams for Epidemiologic Research
• Confounding and collapsibility in causal inference
• Graphs, Causality, and Structural Equation Models
• Finding Minimal D-separators
• Why there is no statistical test for confounding, why many think there is, and why they are almost right
• Testing regression models with fewer regressors
• Probabilities Of Causation: Three Counterfactual Interpretations And Their Identification
• Statistics, Causality, and Graphs
• Simpson's paradox: An anatomy
• Reasoning with Cause and Effect
• Reasoning with Cause and Effect (Transcript of lecture given at IJCAI-99, Stockholm, Sweden, on 4 August 1999)
• Causes and explanations: A structural-model approach − Part I: Causes
• Causes and explanations: A structural-model approach − Part I: Causes (Technical Report)
• Causes and explanations: A structural-model approach − Part II: Causes
• Causes and explanations: A structural-model approach − Part II: Causes (Technical Report)
• Instrumentality Tests Revisited
• A Calculus for Causal Relevance
• The Logic of Counterfactuals in Causal Inference (Discussion of 'Causal Inference without Counterfactuals' by A.P. Dawid)
• Pearl: Comment
• Probabilities of causation: Bounds and identification
• Probabilities of causation: Bounds and identification (Technical Report)
• Direct and Indirect Effects(In Proceedings of the American Statistical Association Joint Statistical Meetings, Minneapolis, MN: MIRA Digital Publishing, 1572-1581, 2005)
• Direct and Indirect Effects (In Proceedings of the Seventeenth Conference on Uncertainy in Artificial Intelligence, San Francisco, CA: Morgan Kaufmann, 411, 20, 2001.)
• Parameter Identification: A New Perspective (Second Draft)
• Bayesian Networks (Technical Report)
• Exogeneity and Superexogeneity: A No-tear Perspective
• On Two Pseudo-Paradoxes in Bayesian Analysis
• Causal Discovery from Changes
• Bayesian Networks, Causal Inference and Knowledge Discovery
• Causal Inference in the Health Sciences: A Conceptual Introduction
• Comments on Seeing and Doing
• Comments on Nozer Singpurwalla's "On Causality and Causal Mechanisms"
• Bayesianism and Causality, or, Why I am Only a Half-Bayesian
• Causal Inference in Statistics: A Gentle Introduction
• A General Identification Condition for Causal Effects
• A New Identification Condition for Recursive Models With Correlated Errors
• A Graphical Criterion for the Identification of Causal Effects in Linear Models
• A New Characterization of the Experimental Implications of Causal Bayesian Networks
• Causality and Counterfactuals in the Situation Calculus
• Strategies for Determining Causes of Events
• Generalized Instrumental Variables
• Qualitative MDPs and POMDPs - An Order of Magnitude Approximation
• On the Testable Implications of Causal Models with Hidden Variables
• Reply to Woodward
• Studies in Causal Reasoning and Learning
• Comments on Neuberg's Review of Causality
• Clarifying the Usage of Structural Models for Commonsense Causal Reasoning
• LAYERWIDTH: Analysis of a New Metric for Directed Acyclic Graphs
• Graphical Methods for Identification in Structural Equation Models
• Modeling and Solving Sequential Decision Problems with Uncertainty and Partial Information
• Faster Heuristic Search Algorithms for Planning with Uncertainty and Full Feedback
• GPT Meets PSR
• Labeled RTDP: Improving the Convergence of Real-Time Dynamic Programming
• Robustness of Causal Claims
• Identifiability of Path-Specific Effects (In Proceedings of International Joint Conference on Artificial Intelligence, Edinburgh, Schotland, 357-363, August 2005)
• Identifiability of Path-Specific Effects (Shortened version to appear In Proceedings of International Joint Conference on Artificial Intelligence, Edinburgh, Schotland, 2005)
• What's in a translation rule?
• Influence Diagrams − Historical and Personal Perspectives
• Identification of Joint Interventional Distributions in Recursive Semi-Markovian Causal Models
• A Characterization of Interventional Distributions in Semi-Markovian Causal Models
• Appendum to Identification of Conditional Interventional Distributions
• Identification of Conditional Interventional Distributions
• Two journeys into human reasoning
• Causal Diagrams
• Graphical Condition for Identi cation in Recursive SEM
• What Counterfactuals Can Be Tested
• Bounds on Direct Effects in the Presence of Confounded Intermediate Variables
• Complete Identification Methods for the Causal Hierarchy
• The Mathematics of Causal Inference in Statistics
• The Mathematics of Causal Relations
• Dormant Independence
• Dormant Independence (Shorter version to appear in AAAI-08)
• Reviews Symposium
• Confounding Equivalence in Causal Inference (In P. Grunwald and P. Spirtes, editors, Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence, 433-441. AUAI, Corvallis, OR, 2010)
• Confounding Equivalence in Causal Inference
• Letter To The Editor: Remarks On The Method Of Propensity Score
• Causal Inference
• The Science and Ethics of Causal Modeling
• Myth, Confusion, and Science in Causal Analysis
• Effects of Treatment on the Treated: Identification and Generalization
• Effects of Treatment on the Treated: Identification and Generalization (Extended version)
• Causal inference in statistics: An overview
• The Structural Theory of Causation
• An Introduction to Causal Inference
• The foundations of causal inference
• On a Class of Bias-Amplifying Variables that Endanger Effect Estimates
• On Measurement Bias in Causal Inference
• On the Consistency Rule in Causal Inference: Axiom, Definition, Assumption, or Theorem?
• Physical and Metaphysical Counterfactuals: Evaluating Disjunctive Actions
• The algorithmization of counterfactuals
• Causal Diagrams
• The Mediation Formula: A guide to the assessment of causal pathways in nonlinear models
• Commentator: A Front-End User-Interface Module for Graphical and Structural Equation Modeling
• Measurement bias and effect restoration in causal inference
• Belief Propagation
• Adjustments and their Consequences — Collapsibility Analysis using Graphical Models
• The Causal Foundations of Structural Equation Modeling
• Transportability across studies: A formal approach
• Transportability of Causal and Statistical Relations: A Formal Approach
• External Validity and Transportability: A Formal Approach
• Statistics and Causality: Separated to Reunite —— Commentary on Bryan Dowd's "Separated at Birth"
• The Curse of Free-Will and the Paradox of Inevitable Regret
• Foreword (In Targeted Learning by Mark J. van der Laan and Sherri Rose, Springer, New York, pp. vii--x, 2011)
• The Causal Mediation Formula — A Guide to the Assessment of Pathways and Mechanisms
• Comments and Controversies: Graphical models, potential outcomes and causal inference: Comment on Lindquist and Sobel
• Controlling Selection Bias in Causal Inference
• Principal Stratification – A goal or a tool?
• Local Characterizations of Causal Bayesian Networks
• Invited Commentary: Understanding Bias Amplification
• Some Thoughts Concerning Transfer Learning, with Applications to Meta-analysis and Data-sharing Estimation
• Interpretation and Identification of Causal Mediation (Extended Version)
• Interpretation and Identification of Causal Mediation
• Transportability of Causal Effects: Completeness Results
• Trygve Haavelmo and the Emergence of Causal Calculus
• A note on the pairwise Markov condition in directed Markov fields
• Eight Myths About Causality and Structural Equation Models
• Correlation and Causation – the logic of co-habitation
• Regression and Causation: A Critical Examination of Six Econometrics Textbooks
• Graphoids over Counterfactuals
• Causal Inference by Surrogate Experiments: z-Identifiability
• Book Reviews: Bias and Causation, Models and Judgment for Valid Comparisions by H.I. Weisberg
• External Validity: From Do-Calculus to Transportability Across Populations
• The Do-Calculus Revisited
• A General Algorithm for Deciding Transportability of Experimental Results
• A solution to a class of selection-bias problems
• Detecting Latent Heterogeneity
• Meta-Transportability of Causal Effects: A Formal Approach
• Causal Transportability with Limited Experiments
• Linear Models: A Useful "Microscope" for Causal Analysis
• Graphical Models for Inference with Missing Data
• Comments on 'Surrogate measures and consistent surrogates' (by Tyler VanderWeele)
• Comment on 'Causal inference, probability theory, and graphical insights' (by Stuart G. Baker)
• Structural Counterfactuals: A Brief Introduction
• Comment: Understanding Simpson's Paradox
• On the Testability of Models with Missing Data
• The Mathematics of Causal Inference
• Recoverability and Testability of Missing data: Introduction and Summary of Results
• Transportability from Multiple Environments with Limited Experiments
• Reflections on Heckman and Pinto's "Causal Analysis After Haavelmo"
• Reply to Commentary by Imai, Keele, Tingley, and Yamamoto Concerning Causal Mediation Analysis
• Is Scientific Knowledge Useful for Policy Analysis? A Peculiar Theorem Says: No
• The Deductive Approach to Causal Inference
• Recovering from Selection Bias in Causal and Statistical Inference
• Testable Implications of Linear Structural Equation Models
• Random Bayesian networks with bounded indegree
• Causes of Effects and Effects of Causes (Long version of paper in Journal of Sociological Methods and Research, 44(1): 149-164, 2015)
• Causes of Effects and Effects of Causes
• Graphical Tools for Linear Structural Equation Modeling
• A short note on the virtues of graphical tools
• Causal, Casual and Curious: Lord's Paradox Revisited – (Oh Lord! Kumbaya!)
• In Defense of Unification (Comments on West and Koch's review of Causality)
• A Note on Causes of Effects
• Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data
• Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data
• Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data (Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence, pp. 161-170, 2015)
• Graphical Models for Recovering Probabilistic and Causal Queries from Missing Data
• Transportability from Multiple Environments with Limited Experiments: Completeness Results
• Identification and Overidentification of Linear Structural Equation Models
• Identification and Overidentification of Linear Structural Equation Models (Appendix to paper forthcoming in Neural Information Processing Systems (NIPS) Conference, Advances in Neural Information Processing Systems, Curran Associates, Inc., 2016.)
• Recovering Causal Effects from Selection Bias
• Comment on Ding and Miratrix: "To Adjust or Not to Adjust?"
• Conditioning on Post-treatment Variables
• Graphical Representation of Missing Data Problems
• Exogeneity and Robustness
• Causal inference and the data-fusion problem
• Causal counterfactual theory for the attribution of weather and climate-related eventsg
• Generalizing Experimental Findings
• Missing Data as a Causal and Probabilistic Problem
• Causal Thinking in the Twilight Zone
• Indirect Confounding and Causal Calculus (On three papers by Cox and Wermuth)
• A Linear "Microscope" for Interventions and Counterfactuals
• Bandits with Unobserved Confounders: A Causal Approach
• Incorporating Knowledge into Structural Equation Models using Auxiliary Variables
• Incorporating Knowledge into Structural Equation Models Using Auxiliary Variables
• The Sure-Thing Principle
• The Eight Pillars of Causal Wisdom (Lecture notes for the UCLA WCE conference, April 24, 2017)
• Counterfactual Data-Fusion for Online Reinforcement Learners
• What is Gained from Past Learning
• Graphical Models for Processing Missing Data
• Comments on: The tale wagged by the DAG
• Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution
• A Personal Journey into Bayesian Networks
• Challenging the hegemony of randomized controlled trials: A commentary on Deaton and Cartwright
• RE: A Practical Example Demonstrating the Utility of Single-world Intervention Graphs
• Estimation with Incomplete Data: The Linear Case
• The Seven Tools of Causal Inference, with Reflections on Machine Learning
• Sensitivity Analysis of Linear Structural Causal Models
• Does Obesity Shorten Life? Or is it the Soda? On Non-manipulable Causes
• Sufficient Causes: On Oxygen, Matches, and Fires
• Causal and Counterfactual Inference (Forthcoming section in The Handbook of Rationality)
• On the interpretation of do(x)
• Telling and Re-telling History: The case for a whiggish account of the history of causation
• Unit Selection Based on Counterfactual Logic
• The Limitations Of Opaque Learning Machines
• A Simultaneous Discover-Identify Approach to Causal Inference in Linear Models
• Generalizing Experimental Results by Leveraging Knowledge of Mechanisms
• Searching for an Optimal Path in a Tree with Random Costs
• Complete Identification Methods for Causal Inference
• Statistics and Causal Inference: A Review
• Theoretical Bounds on the Complexity of Inexact Computations
• Causal Discovery from Changes: a Bayesian Approach

Publications

• Deep Learning with Dynamic Computation Graphs
• A Study in Lexical Network Theory
• A Survey of Current Practice and Teaching of AI
• The Unreasonable Effectiveness of Data
• Google's Hybrid Approach to Research
• Six Problems for Story Understanders
• Inference In Text Understanding
• Natural Language Corpus Data
• A Unified Theory of Inference for Text Understanding
• Design Patterns in Dynamic Programming
• The Making of the Gettysburg PowerPoint Presentation
• Building a Large Lexicon with Lexical Network Theory
• LISP − a Language for Internet Scripting and Programming
• Internet-Scale Data Analysis
• Teach Yourself Programming in Ten Years
• Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp
• Marker Passing as a Weak Method for Text lnferencing
• SILK - a playful blend of Scheme and Java
• Techniques for automatic memoization with applications to context-free parsing
• Verbmobil: A Translation System for Face-to-Face Dialog

Publications

• Probabilistic Model-Based Approach for Heart Beat Detection
• State Abstraction for Programmable Reinforcement Learning Agents
• Concurrent Hierarchical Reinforcement Learning
• Global seismic monitoring: A Bayesian approach
• Metaphysics of Planning Domain Descriptions
• A Nearly-Black-Box Online Algorithm for Joint Parameter and State Estimation in Temporal Models
• Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient
• Vertically Integrated Seismological Analysis II: Inference
• Vertically Integrated Seismological Analysis I: Modeling
• Bayesian Inference for Signal-Based Seismic Monitoring
• Optimal composition of real-time systems
• Rationality and Intelligence
• Object Identification: A Bayesian Analysis with Application to Traffic Surveillance.
• Online Bagging and Boosting
• Approximate Inference for Infinite Contingent Bayesian Networks
• Why are DBNs sparse?
• Dynamic Scaled Sampling for Deterministic Constraints
• Signal-based Bayesian Seismic Monitoring
• The Physics of Text: Ontological Realism in Information Extraction
• NET-VISA: Network Processing Vertically Integrated Seismic Analysis
• The Ultimate Pilot Program
• Unifying Logic and Probability
• Markov Chain Monte Carlo Data Association for General Multiple Target Tracking Problems
• Handwriting and Gestures in the Air, Recognizing on the Fly
• Learning agents for uncertain environments (extended abstract)
• Adversarial Training for Relation Extraction
• Bayesian Networks
• Analogy by Similarity
• Machine Learning
• On Some Tractable Cases of Logical Filtering
• Angelic Semantics for High-Level Actions
• Exploiting Belief State Structure in Graph Search
• Angelic Hierarchical Planning: Optimal and Online Algorithms
• Combined Task and Motion Planning for Mobile Manipulation
• Using Classical Planners for Tasks with Continuous Operators in Robotics
• Bayesian Relational Memory for Semantic Visual Navigation
• The Extended Parameter Filter
• Efficient Cooperative Inverse Reinforcement Learning
• An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning
• Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms
• Policy invariance under reward transformations: Theory and application to reward shaping
• Combined Task and Motion Planning Through an Extensible Planner-Independent Interface Layer
• Identity Uncertainty
• Approximate inference for first-order probabilistic languages
• Logical Filtering
• BLOG: Probabilistic Models with Unknown Objects
• Concurrent Hierarchical Reinforcement Learning
• Efficient belief-state AND–OR search, with application to Kriegspiel
• Writing Stratagus-playing Agents in Concurrent ALisp
• Bounded Intention Planning
• Markovian State and Action Abstractions for MDPs via Hierarchical MCTS
• Swift: Compiled Inference for Probabilistic Programming Languages
• Efficient Reinforcement Learning with Hierarchies of Machines by Leveraging Internal Transitions
• Should Robots be Obedient?
• The Off-Switch Game
• Provably beneficial artificial intelligence
• Planning Using Multiple Execution Architectures
• Local learning in probabilistic networks with hidden variables
• The BATmobile: Towards a Bayesian Automated Taxi
• Rationality and Intelligence
• Approximating Optimal Policies for Partially Observable Stochastic Domains
• Convergence of reinforcement learning with general function approximators
• Tracking many objects with many sensors
• Unifying Logic and Probability: A New Dawn for AI?
• Provably bounded optimal agents
• Experimental Comparisons of Online and Batch Versions of Bagging and Boosting
• Adversarial Policies: Attacking Deep Reinforcement Learning
• Statistical Visual Language Models for Ink Parsing
• Temporal Logical Filtering – Preliminary Results
• Computational Intelligence
• Metareasoning
• Algorithms for inverse reinforcement learning
• Q-Decomposition for Reinforcement Learning Agents
• Probabilistic modeling of sensor artifacts in critical care
• Bayesian Treaty Monitoring: Preliminary Report
• Machine Learning at the CTBTO. Testing and evaluation of the False Events Identification (FEI) and Vertically Integrated Seismic Association (VISA) project
• Analyst Evaluation of NET-VISA (Network Processing Vertically Integrated Seismic Analysis) at the CTBTO
• Progress in Signal-Based Bayesian Monitoring
• Model Based Probabilistic Inference for Intensive Care Medicine
• Programmable Reinforcement Learning Agents
• Identity Uncertainty and Citation Matching
• Distance metric learning, with application to clustering with side-information
• A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences
• Probabilistic detection of short events, with application to critical care monitoring
• Global seismic monitoring as probabilistic inference
• Multilinear Dynamical Systems for Tensor Time Series
• Combined State and Parameter Estimation of Human Intracranial Hemodynamics
• Gaussian Process Random Fields
• Inverse Reward Design
• Learning Plannable Representations with Causal InfoGAN
• Meta-Learning MCMC Proposals
• Negotiable Reinforcement Learning for Pareto Optimal Sequential Decision-Making
• Extending Bayesian Networks to the Open-Universe Case
• Rationality and Intelligence: A Brief Update
• Speeding Up HAM Learning with Internal Transitions
• Provably Beneficial Artificial Intelligence
• Cooperative Inverse Reinforcement Learning
• Should we fear supersmart robots?
• Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
• Machine learning for Comprehensive Nuclear-Test-Ban Treaty monitoring
• First-Order Probabilistic Models for Information Extraction
• BLOG: Relational Modeling with Unknown Objects
• Anytime Lifted Belief Propagation
• BLOG: ProbabilisticModels with Unknown Objects
• First-Order Models for POMDPs
• Uncertain observation times
• State Abstraction for Programmable Reinforcement Learning Agents
• Angelic Semantics for High-Level Actions
• Angelic Hierarchical Planning: Optimal and Online Algorithms (Revised)
• Markov Chain Monte Carlo Data Association for Multiple-Target Tracking
• Variational MCMC
• Decayed MCMC Filtering
• A generalized mean field algorithm for variational inference in exponential families
• Efficient Gradient Estimation for Motor Control Learning
• Graph partition strategies for generalized mean field inference
• General-Purpose MCMC Inference over Relational Structures
• A Compact, Hierarchically Optimal Q-function Decomposition
• Improving Gradient Estimation by Incorporating Sensor Data
• Gibbs Sampling in Open-Universe Stochastic Languages
• RAPID: A Reachable Anytime Planner for Imprecisely-sensed Domains
• A temporally abstracted Viterbi algorithm
• Selecting Computations: Theory and Applications
• Fast Gaussian Process Posteriors with Product Trees
• First-Order Open-Universe POMDPs
• Multitasking: Efficient Optimal Planning for Bandit Superprocesses
• A Smart-Dumb/Dumb-Smart Algorithm for Efficient Split-Merge MCMC
• Image Segmentation in Video Sequences: A Probabilistic Approach

Publications

• Why does deep and cheap learning work so well?
• Life 3.0 : being human in the age of artificial intelligence
• Research Priorities for Robust and Beneficial Artificial Intelligence

• Language Identification in the Limit
• The Working Set Model for Program Behavior
• An Implementation of a Log-Structured File System for UNIX
• A statistical interpretation of term specificity and its application in retrieval
• Password Security: A Case History
• The Case for a Single-Chip Multiprocessor
• Fundamental Concepts in Programming Languages
• On the Translation of Languages from Left to Right
• A Vector Space Model for Automatic Indexing
• Semantics of Context-Free Languages
• The Entity-Relationship Model-Toward a Unified View of Data
• The Nucleus of a Multiprogramming System
• The Complexity of Theorem - Proving Procedures
• How to construct random functions
• Remembrance of Data Passed: A Study of Disk Sanitization Practices
• The FORTRAN Automatic Coding System
• A Unified Approach to Global Program Optimization
• An Iterative Image Registration Technique with an Application to Stereo Vision
• Validity of the single processor approach to achieving large scale computing capabilities
• Architecture of the IBM System / 360
• A Machine Program for Theorem-Proving
• Artificial Intelligence: A Modern Approach
• A Machine-independent theory of the complexity of recursive functions
• A Training Algorithm for Optimal Margin Classifiers
• No Silver Bullet — Essence and Accident in Software Engineering
• Knowledge-based analysis of microarray gene expression data by using support vector machines
• Thirty Years Later: Lessons from the Multics Security Evaluation
• The Intrinsic Computational Difficulty of Functions
• A Relational Model of Data for Large Shared Data Banks
• Relational Completeness of Data Base Sublanguages
• Comprehending monads
• A Note on the Confinement Problem
• An Experimental Time-Sharing System
• Scheduling Techniques for Concurrent Systems
• The CRAY - 1 Computer System
• Cryptographic Limitations on Learning Boolean Formulae and Finite Automata
• Hierarchical Program Structures
• A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence
• Design Patterns: Elements of Reusable Object-Oriented Software
• Go To Statement Considered Harmful
• Probabilistic Reasoning in Intelligent Systems
• A fast learning algorithm for deep belief nets
• Federated Database Systems for Managing Distributed, Heterogeneous, and Autonomous Databases
• A Fast File System for UNIX
• Assigning Meanings to Programs
• Learnability and the Vapnik-Chervonenkis Dimension
• An Empirical Study of the Robustness of Windows NT Applications Using Random Testing
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Weighted Voting for Replicated Data
• The Knowledge Complexity of Interactive Proof-Systems
• An axiomatic basis for computer programming
• Determining Optical Flow
• A Method for the Construction of Minimum-Redundancy Codes
• Algorithmic Information Theory
• Object Recognition from Local Scale-Invariant Features
• An Inductive Inference Machine
• CONDENSATION — Conditional Density Propagation for Visual Tracking
• Soft Updates: A Solution to the Metadata Update Problem in File Systems
• First Draft of a Report on the EDVAC
• Snakes: Active Contour Models
• The Phase Correlation Image Alignment Method
• The Next 700 Programming Languages
• Formal Definition of ALGOL 60
• The Design and Implementation of a Log-Structured File System
• Linear Logic
• Learning Quickly When Irrelevant Attributes Abound: A New Linear-threshold Algorithm
• Recursive functions of symbolic expressions and their computation by machine, Part I
• Experience with Processes and Monitors in Mesa
• Microkernel operating system architecture and Mach
• A Description of the Model-View-Controller User Interface Paradigm in the Smalltalk-80 System
• Software Engineering
• Realization of Natural Language Interfaces Using Lazy Functional Programming
• The Notions of Consistency and Predicate Locks in a Database System
• Operating System Principles
• The Emperor's Old Clothes
• A Program Data Flow Analysis Procedure
• Virtual Memory, Processes, and Sharing in MULTICS
• A Technique for Software Module Specification with Examples
• Reflections on Trusting Trust
• Extended Boolean Information Retrieval
• gprof: a Call Graph Execution Profiler
• Collaborative Networks: Value creation in a knowledge society
• On the criteria to be used in decomposing systems into modules
• The Laplacian Pyramid as a Compact Image Code
• Induction of Decision Trees
• A Case for Redundant Arrays of Inexpensive Disks (RAID)
• The Cathedral and the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary
• The Rendering Equation
• Comments on "the Case for the Reduced Instruction Set Computer"
• The case for the reduced instruction set computer
• Finite Automata and Their Decision Problems
• Learning Internal Representations by Error Propagation
• SEQUEL: A Structured English Query Language
• Structure and Interpretation of Computer Programs
• Elastically Deformable Models
• Mining Association Rules between Sets of Items in Large Databases
• Sketchpad: A man-machine graphical communication system
• Statecharts: A Visual Formalism For Complex Systems
• The Strength of Weak Learnability
• Learning to Predict by the Methods of Temporal Differences
• The Mythical Man-Month: Essays on Software Engineering
• Secrecy, Authentication, And Public Key Systems
• On Computable Numbers, with an Application to the Entscheidungsproblem
• Computing Machinery and Intelligence
• Two-level morphology: A general computational model of word-form recognition and production
• The UNIX Time-Sharing System
• A Theory of the Learnable
• Yacc: Yet Another Compiler-Compiler
• Fuzzy sets
• Introduction to Automata Theory, Languages, and Computation
• Reducibility among combinatorial problems
• Decidability of Second-Order Theories and Automata on Infinite Trees
• On Certain Formal Properties of Grammars
• Cutland's Computability: An Introduction to Recursive Function Theory

Publications

• Generalized Harmonic Analysis
• Extrapolation, Interpolation, and Smoothing of Stationary Time Series: With Engineering Applications
• Nonlinear Problems in Random Theory
• Cybernetics: Or Control and Communication in the Animal and the Machine
• Wiener on the Fourier Integral
• The Human Use of Human Beings

Publications

• A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, August 31, 1955
• The Philosophy of PCM
• Scientific Aspects of Juggling
• Collected Papers of Claude Elwood Shannon
• A Mathematical Theory of Communication
• Computability and Probabilistic machines
• A Symmetrical Notation for Numbers
• A Universal Turing Machine with Two Internal States
• Prediction and Entropy of Printed English
• Communication in the Presence of Noise
• Zero error capacity of a noisy channel
• A Symbolic Analysis of Relay and Switching Circuits
• A Mathematical Theory of Cryptography
• Coding Theorems for a Discrete Source With a Fidelity Criterion
• Lower Bounds to Error Probability for Coding on Discrete Mernoryless Channels. I
• Lower Bounds to Error Probability for Coding on Discrete Memoryless Channels. II
• Communication Theory of Secrecy Systems
• Two-way communication channels
• Programming a Computer for Playing Chess

Publications

• Anatomy and Physiology of Vision in the Frog (Rana pipiens)
• Chemical transmission in the nose of the frog
• What the Frog's Eye Tells the Frog's Brain
• A Logical Calculus of the Ideas Immanent in Nervous Activity
• Why the Mind Is in the Head
• Warren S. McCulloch Papers
• A heterarchy of values determined by the topology of nervous nets
• Recollections of the Many Sources of Cybernetics
• What is a number that a man may know it, and a man, that he may know a number?

Publications

• Computation: Finite and Infinite Machines
• The Turing Option
• Steps Toward Artificial Intelligence
• Future of AI Technology
• Why People Think Computers Can't
• Understanding Musical Activities: Readings In AI And Music
• Matter, Mind and Models
• Music, Mind, and Meaning
• Symbolic vs. Connectionist
• Alienable Rights
• A Framework for Representing Knowledge
• Progress Report on Artificial Intelligence
• Telepresence
• Virtual Molecular Reality
• Afterword to Vernor Vinge's novel, "True Names"
• Form and Content in Computer Science
• Memoir on Inventing the Confocal Scanning Microscope
• Negative Expertise
• Jokes and their Relation to the Cognitive Unconscious
• Introduction to LogoWorks
• Will Robots Inherit the Earth?
• Interior Grounding, Reflection, and Self-Consciousness
• Communication with Alien Intelligence
• An Interview With Marvin L. Minsky
• Perceptions: An Introduction to Computational Geometry
• The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind
• The Society of Mind
• BBC-3 Music Interview 2004

Publications

• On the analysis of human problem solving protocols
• Human problem solving: The state of the theory in 1970
• Computer Structures: Readings and Examples
• The Processes of Creative Thinking
• IPL- V Programmer's Reference Manual
• The Psychology of Human-Computer Interaction
• Unified Theories of Cognition
• Universal Subgoaling and Chunking: The Automatic Generation and Learning of Goal Hierarchies
• Reasoning, problem solving and decision processes: the problem space as a fundamental category
• Chess-playing Programs And The Problem Of Complexity
• Computer Science as Empirical Inquiry: Symbols and Search
• SOAR: An Architecture for General Intelligence
• The Keystroke-Level Model for User Performance Time with Interactive Systems
• You can't play 20 questions with nature and win: projective comments on the papers of this symposium
• The Knowledge Level
• GPS, A Program that Simulates Human Thought
• Programming the Logic Theory Machine
• A general problem-solving program for a computer
• Heuristic programming: ill-structured problems
• Computer Text-Editing: An Information-Processing Analysis of a Routine Cognitive Skill
• Elements of a Theory of Human Problem Solving
• Mechanisms of skill acquisition and the law of practice
• Heuristic Problem Solving: The Next Advance in Operations Research
• Physical symbol systems
• The ZOG approach to man-machine communication
• Formulating the Problem-Space Computational Model
• Models: Their Uses And Limitations
• What is Computer Science?
• Harpy, production systems and human cognition
• Intellectual issues in the history of artificial intelligence
• The Search for Generality
• A preliminary analysis of the Soar architecture as a basis for general intelligence
• How can Merlin understand?
• Initial Assessment of Architectures for Production Systems
• The chunking of goal hierarchies: a generalized model of practice
• R1-Soar: An Experiment in Knowledge-Intensive Programming in a Problem-Solving Architecture
• Information Processing Language V Manual
• Skill in Chess
• Rational Choice and the Structure of the Environment
• Altruism and Economics
• Perception in Chess
• Verbal Reports as Data
• A Behavioral Model of Rational Choice
• On a Class of Skew Distribution Functions
• The Architecture of Complexity
• Expert and Novice Performance in Solving Physics Problems
• On the Concept of Organizational Goal
• Models of man: social and rational
• How Big Is a Chunk?
• Making Management Decisions: the Role of Intuition and Emotion
• Theories of bounded rationality
• Why Are Some Problems Hard? Evidence from Tower of Hanoi
• Why a Diagram is (Sometimes) Worth Ten Thousand Words
• Models of My Life
• Organizations and Markets
• What Is An "Explanation" Of Behavior?
• A Formal Theory of the Employment Relationship
• The Sciences of the Artificial
• Motivational and emotional controls of cognition
• Theories of Decision-Making in Economics and Behavioral Science
• Administrative Behavior: How organizations can be understood in terms of decision processes
• Models of Competence in Solving Physics Problems

Publications

• Teaching Children to be Mathematicians Versus Teaching About Mathematics
• Mindstorms: children, computers, and powerful ideas
• Computer Criticism vs. Technocentric Thinking
• One AI or Many?
• Microworlds: transforming education
• Perceptrons: An Introduction to Computational Geometry
• The Children's Machine: Rethinking School In The Age Of The Computer
• The Connected Family: Bridging the Digital Generation Gap

Publications

• Connectivity of random nets
• Inductive inference research status, spring 1967
• The Application of Algorithmic Probability to Problems in Artificial Intelligence
• A Formal Theory of Inductive Inference, Part I
• A Formal Theory of Inductive Inference, Part II
• A Progress Report on Machines to Learn to Translate Languages and Retrieve Information
• The Adequacy of Complexity Models of Induction
• An Inductive Inference Machine
• The Discovery of Algorithmic Probability
• A Coding Method for Inductive Inference
• Two Kinds of Probabilistic Induction
• Machine Learning − Past and Future
• An Exact Method for the Computation of the Connectivity of Random Nets
• Effect of Heisenberg's Principal on Channel Capacity
• A System for Incremental Learning Based on Algorithmic Probability
• Lecture 1: Algorithmic Probability
• Lecture 2: Applications of Algorithmic Probability
• Does Algorithmic Probability Solve the Problem of Induction?
• The Universal Distribution and Machine Learning
• Progress Report: Research in Inductive Inference For the Year Ending 31 March 1959
• A New Method for Discovering the Grammars of Phrase Structure Languages
• Progress In Incremental Machine Learning
• Optimum Sequential Search
• Perfect Training Sequences and the Costs of Corruption - A Progress Report on Inductive Inference Research
• The Probability of "Undefined" (Non-converging) Output in Generating the Universal Probability Distribution
• Progress Report: Research in Inductive Inference April 1959 to November 1960
• A Preliminary Report on a General Theory of Inductive Inference
• The Search for Artificial Intelligence
• Complexity-Based Induction Systems: Comparisons and Convergence Theorems
• Some Recent Work in Artificial Intelligence
• Structure of Random Nets
• Inductive Inference Theory - A Unified Approach to Problems in Pattern Recognition and Artificial Intelligence
• The Mechanization of Linguistic Learning
• The Time Scale of Artificial Intelligence: Reflections on Social Effects
• Training Sequences for Mechanized Induction
• Comments on Dr. S. Watanabe's Paper
• Autonomous Theory Building Systems
• Algorithmic Probability, Heuristic Programming and AGI

Publications

• Speechstuff and Thoughtstuff: Musings on the Resonances Created by Words and Phrases via the Subliminal Perception of their Buried Parts
• A Non-deterministic Approach To Analogy, Involving The Ising Model Of Ferromagnetism
• Alan Turing: The Enigma
• Godel, Escher, Bach: An Eternal Golden Braid
• Gödel's Proof
• To Err is Human - To Study Error-making is Cognitive Science
• I Am a Strange Loop
• Metamagical Themas: Questing For The Essence Of Mind And Pattern
• Analogy as the Core of Cognition
• on seeing A's and seeing As
• The Mind's I: Fantasies and Reflections on Self and Soul

Publications

• A Robust Layered Control System for a Mobile Robot
• A Robot that Walks; Emergent Behavior from a Carefully Evolved Network
• Building Brains for Bodies
• The Intelligent Room Project
• From Earwigs to Humans
• Model-Based Three-Dimensional Interpretations of Two-Dimensional Images
• Intelligence Without Reason
• Challenges for Complete Creature Architectures
• The Cog Project: Building a Humanoid Robot
• The Role of Learning in Autonomous Robots
• Elephants Don't Play Chess
• Fast, Cheap And Out Of Control: A Robot Invasion Of The Solar System
• Visually-Guided Obstacle Avoidance in Unstructured Environments
• Alternative Essences of Intelligence
• How to Build Complete Creatures Rather than Isolated Cognitive Simulators
• Technologies for Human/Humanoid Natural Interactions
• Humanoid Robots: A New Kind of Tool
• Learning to Coordinate Behaviors
• The relationship between matter and life
• From robot dreams to reality
• New Approaches to Robotics
• Prospects for Human Level Intelligence for Humanoid Robots
• Artificial Life and Real Robots
• Intelligence without representation
• Small Planetary Rovers
• Integrated Systems Based on Behaviors
• The whole iguana
• A Subdivision Algorithm in Configuration Space for Findpath with Rotation
• Planning Collision-Free Motions for Pick-and-Place Operations
• The Behavior Language; User's Guide
• Sensing and Manipulating Built-For-Human Environments
• Symbolic Error Analysis and Robot Planning
• Achieving Artificial Intelligence Through Building Robots
• A Robot That Walks; Emergent Behaviors from a Carefully Evolved Network?
• Twilight Zones and Cornerstones: A Gnat Robot Double Feature
• Planning Is Just A Way Of Avoiding Figuring Out What To Do Next
• Cambrian Intelligence: The Early History of the New AI
• Robotics Research: Results of the 12th International Symposium ISRR
• The Artificial Life Route To Artificial Intelligence: Building Embodied, Situated Agents

Publications

• Deep Learning of Representations: Looking Forward
• Visualizing Higher-Layer Features of a Deep Network
• Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach
• Contractive Auto-Encoders: Explicit Invariance During Feature Extraction
• Practical Recommendations for Gradient-Based Training of Deep Architectures
• Representation Learning: A Review and New Perspectives
• Theano: new features and speed improvements
• High-dimensional sequence transduction
• Maxout Networks
• Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
• How to Construct Deep Recurrent Neural Networks
• Neural Machine Translation by Jointly Learning to Align and Translate
• On the Properties of Neural Machine Translation: Encoder–Decoder Approaches
• How transferable are features in deep neural networks?
• Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
• FitNets: Hints for Thin Deep Nets
• Gated Feedback Recurrent Neural Networks
• Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
• End-to-end attention-based large vocabulary speech recognition
• Binarized Neural Networks: Training Neural Networks with Weights and Activations Constrained to +1 or -1
• The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
• Inference for the Generalization Error
• A Structured Self-attentive Sentence Embedding
• Graph Attention Networks
• Curriculum Learning
• Learning Structured Embeddings of Knowledge Bases
• Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering
• Algorithms for Hyper-Parameter Optimization
• On the Number of Linear Regions of Deep Neural Networks
• Generative Adversarial Nets
• BinaryConnect: Training Deep Neural Networks with binary weights during propagations
• Attention-Based Models for Speech Recognition
• Building End-to-End Dialogue Systems: Using Generative Hierarchical Neural Network Models
• A Neural Probabilistic Language Model
• Deep Learning of Representations for Unsupervised and Transfer Learning
• Scaling Learning Algorithms towards AI
• Random Search for Hyper-Parameter Optimization
• Gradient Flow in Recurrent Nets: the Difficulty of Learning Long-Term Dependencies
• Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
• Convergence Properties of the K-Means Algorithms
• Deep Learning
• An Empirical Evaluation of Deep Architectures on Problems with Many Factors of Variation
• Why Does Unsupervised Pre-training Help Deep Learning?
• Understanding the difficulty of training deep feedforward neural networks
• Deep Sparse Rectifier Neural Networks
• No Unbiased Estimator of the Variance of K-Fold Cross-Validation
• Hierarchical Probabilistic Neural Network Language Model
• Extracting and Composing Robust Features with Denoising Autoencoders
• Classification using Discriminative Restricted Boltzmann Machines
• Exploring Strategies for Training Deep Neural Networks
• Gradient Based Learning Applied to Document Recognition
• Convolutional networks for images, speech, and time series
• Word representations: A simple and general method for semi-supervised learning
• On Using Very Large Target Vocabulary for Neural Machine Translation
• Representational Power of Restricted Boltzmann Machines and Deep Belief Networks
• Unsupervised Feature Learning and Deep Learning: A Review and New Perspectives
• Using Recurrent Neural Networks for Slot Filling in Spoken Language Understanding
• Theano: A CPU and GPU Math Compiler in Python
• Learning long-term dependencies with gradient descent is difficult
• Learning Deep Architectures for AI
• A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues
• Kernel Matching Pursuit
• Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
• Markovian Models for Sequential Data
• Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing
• What Regularized Auto-Encoders Learn from the Data Generating Distribution
• Advances in Optimizing Recurrent Networks
• A Semantic Matching Energy Function for Learning with Multi-relational Data
• An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks
• Training deep neural networks with low precision multiplications
• A Recurrent Latent Variable Model for Sequential Data
• Hierarchical Multiscale Recurrent Neural Networks
• Plug and Play Generative Networks: Conditional Iterative Generation of Images in Latent Space
• A Parallel Mixture of SVMs for Very Large Scale Problems
• Semi-supervised Learning by Entropy Minimization
• Greedy Layer-Wise Training of Deep Networks
• Generalized Denoising Auto-Encoders as Generative Models
• Boosting Neural Networks
• The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training
• An Input Output HMM Architecture
• Input/Output HMMs for Sequence Processing
• Object Recognition with Gradient-Based Learning
• On the difficulty of training recurrent neural networks
• Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Publications

• What If AI Succeeds? The Rise of the Twenty-First Century Artilect
• The 21st. CENTURY ARTILECT: Moral Dilemmas Concerning the Ultra Intelligent Machine
• THE ARTILECT WAR: Cosmists vs. Terrans
• A world survey of artificial brain projects, Part I: Large-scale brain simulations
• Artificial Embryology - The Genetic Programming of an Artificial Embryo
• Machines Like Us interviews: Hugo de Garis
• The Evolution of Robust, Reversible, Nano-Scale, Femto-Second-Switching Circuits
• Porting a Cellular Automata Based Artificial Brain to MIT's Cellular Automata Machine 'CAM-8'
• The CAM-Brain Machine (CBM): An FPGA Based Tool for Evolving a 75 Million Neuron Artificial Brain to Control a Lifesized Kitten Robot
• Reversible Computing for Beginners
• BRAD, Multi-ism, Culture Bashing and PC
• An Overview of Evolutionary Computation
• The Second International Conference on Artificial General Intelligence (AGI-09)

Publications

• Who Said What: Modeling Individual Labelers Improves Classification
• CvxNet: Learnable Convex Decomposition
• Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions
• Cerberus: A Multi-headed Derenderer
• Deep learning
• Similarity of Neural Network Representations Revisited
• Stacked Capsule Autoencoders
• Dynamic Routing Between Capsules
• A Fast Learning Algorithm for Deep Belief Nets
• When Does Label Smoothing Help?
• Learning Energy-Based Models of High-Dimensional Data
• Layer Normalization
• Matrix Capsules with EM Routing
• Lookahead Optimizer: k steps forward, 1 step back
• To Recognize Shapes, First Learn to Generate Images
• Learning multiple layers of representation
• Reducing the Dimensionality of Data with Neural Networks
• Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
• Using FastWeights to Attend to the Recent Past
• Large scale distributed neural network training through online distillation
• Where do features come from?
• Illustrative Language Understanding: Large-Scale Visual Grounding with Image Search
• Neural Networks for Machine Learning
• How Learning Can Guide Evolution
• Classical and Bayesian Inference in Neuroimaging: Theory
• Boltzmann machines: Constraint satisfaction networks that learn
• Deep Belief Networks for phone recognition
• Feudal Reinforcement Learning
• Using Very Deep Autoencoders for Content-Based Image Retrieval
• Glove-Talk: a neural network interface between a data-glove and a speech synthesizer
• On the importance of initialization and momentum in deep learning
• Deep Belief Nets
• Parallel visual computation
• How Neural Networks Learn from Experience
• Semantic Hashing
• NeuroAnimator: Fast Neural Network Emulation and Control of Physics-Based Models
• Acoustic Modeling using Deep Belief Networks
• The wake-sleep algorithm for unsupervised neural networks

Publications

• Predicting Deeper into the Future of Semantic Segmentation
• Model-Based Planning with Discrete and Continuous Actions
• Adversarially Regularized Autoencoders
• Which Encoding is the Best for Text Classification in Chinese, English, Japanese and Korean?
• A hierarchical loss and its problems when classifying non-hierarchically
• Prediction Under Uncertainty with Error-Encoding Networks
• A Closer Look at Spatiotemporal Convolutions for Action Recognition
• Byte-Level Recursive Convolutional Auto-Encoder for Text
• Comparing Dynamics: Deep Neural Networks versus Glassy Systems
• Predicting Future Instance Segmentation by Forecasting Convolutional Features
• Design Inspiration from Generative Networks
• Towards Understanding the Role of Over-Parametrization in Generalization of Neural Networks
• Backpropagation for Implicit Spectral Densities
• GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations
• Adversarially-Trained Normalized Noisy-Feature Auto-Encoder for Text Generation
• A Spectral Regularizer for Unsupervised Disentanglement
• Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic
• Learning about an exponential amount of conditional distributions
• Unsupervised Image Matching and Object Discovery as Optimization
• Inspirational adversarial image generation

Publications

• How Hard is Artificial Intelligence? Evolutionary Arguments and Selection Effects
• Observer-Relative Chances In Anthropic Reasoning?
• The Doomsday Argument, Adam & Eve, UN⁺⁺, and Quantum Joe
• The Doomsday Argument is Alive and Kicking
• The Ethics of Artificial Intelligence
• Cognitive Enhancement: Methods, Ethics, Regulatory Challenges
• Converging Cognitive Enhancements
• Drugs can be used to treat more than disease
• Embryo Selection for Cognitive Enhancement: Curiosity or Game-changer?
• Existential Risk Prevention as a Global Priority
• Quantity of experience: brain-duplication and degrees of consciousness
• Where Are They? Why I Hope the Search for Extraterrestrial Life Finds Nothing
• Infinite Ethics
• Information Hazards: A Typology of Potential Harms from Knowledge
• The Mysteries of Self-Locating Belief and Anthropic Reasoning
• The Meta-Newcomb Problem
• Astronomical Waste: The Opportunity Cost of Delayed Technological Development
• In Defense of Posthuman Dignity
• What is a Singleton?
• How long before superintelligence?
• Thinking Inside the Box: Controlling and Using an Oracle AI
• Pascal's mugging
• Are You Living in a Computer Simulation?
• The Reversal Test: Eliminating Status Quo Bias in Applied Ethics
• The Superintelligent Will: Motivation and Instrumental Rationality in Advanced Artificial Agents
• Sleeping Beauty and Self-Location: A Hybrid Model
• Why We Need Friendly AI

Publications

• Building Watson: An Overview of the DeepQA Project
• Watson: Beyond Jeopardy!
• Overview of Component Services for Knowledge Integration in UIMA (a.k.a. SUKI)

Lecture Notes

• 01 and 02: Introduction, Regression Analysis and Gradient Descent
• 03: Linear Algebra - review
• 04: Linear Regression with Multiple Variables
• 05: Octave
• 06: Logistic Regression
• 07: Regularization
• 08: Neural Networks - Representation
• 09: Neural Networks - Learning
• 10: Advice for applying machine learning techniques
• 11: Machine Learning System Design
• 12: Support Vector Machines
• 13: Clustering
• 14: Dimensionality Reduction
• 15: Anomaly Detection
• 16: Recommender Systems
• 17: Large Scale Machine Learning
• 18: Application Example - Photo OCR
• Understanding Andrew Ng's Machine Learning Course – Notes and codes

Publications

• Robust textual inference via learning and abductive reasoning
• Efficient L₁ Regularized Logistic Regression
• A Fast Data Collection and Augmentation Procedure for Object Recognition
• Learning Grasp Strategies with Partial Shape Information
• Make3D: Depth Perception from a Single Still Image
• Applying Online Search Techniques to Continuous-State Reinforcement Learning
• Semantic Taxonomy Induction from Heterogenous Evidence
• Learning Word Vectors for Sentiment Analysis
• Apprenticeship Learning for Helicopter Control
• An Analysis of Single-Layer Networks in Unsupervised Feature Learning
• Spam Deobfuscation using a Hidden Markov Model
• groupTime: Preference-Based Group Scheduling
• An Experimental and Theoretical Comparison of Model Selection Methods
• Preventing "Overfitting" of Cross-Validation data
• Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data
• A dynamic Bayesian network model for autonomous 3d reconstruction from a single indoor image
• A Steiner tree approach to efficient object detection
• Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis
• Integrating Visual and Range Data for Robotic Object Detection
• Robust textual inference via graph matching
• Solving the Problem of Cascading Errors: Approximate Bayesian Inference for Linguistic Annotation Pipelines
• Learning to Merge Word Senses
• Cheap and Fast—But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks
• Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions
• Semantic Compositionality through Recursive Matrix-Vector Spaces
• Autonomous Helicopter Tracking and Localization Using a Self-Surveying Camera Array
• Learning 3-D Scene Structure from a Single Still Image
• 3-D Reconstruction from Sparse Views using Monocular Vision
• Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning
• Algorithms for inverse reinforcement learning
• Convergence rates of the Voting Gibbs classifier, with application to Bayesian feature selection
• Apprenticeship Learning via Inverse Reinforcement Learning
• Feature selection, L₁ vs. L₂ regularization, and rotational invariance
• Learning Random Walk Models for Inducing Word Dependency Distributions
• Online and Batch Learning of Pseudo-Metrics
• Exploration and Apprenticeship Learning in Reinforcement Learning
• High Speed Obstacle Avoidance using Monocular Vision and Reinforcement Learning
• Constructing Informative Priors using Transfer Learning
• Using Inaccurate Models in Reinforcement Learning
• Using Inaccurate Models in Reinforcement Learning (Extended Version)
• Learning for Control from Multiple Demonstrations
• Space-indexed Dynamic Programming: Learning to Follow Trajectories
• Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations
• Large-scale Deep Unsupervised Learning using Graphics Processors
• A majorization-minimization algorithm for (multiple) hyperparameter learning
• Near-Bayesian Exploration in Polynomial Time
• Regularization and Feature Selection in Least-Squares Temporal Difference Learning
• Parsing Natural Scenes and Natural Language with Recursive Neural Networks
• Building High-level Features Using Large Scale Unsupervised Learning
• On Feature Selection: Learning with Exponentially many Irrelevant Features as Training Examples
• Improving Text Classification by Shrinkage in a Hierarchy of Classes
• End-to-End Text Recognition with Convolutional Neural Networks
• Quadruped Robot Obstacle Negotiation via Reinforcement Learning
• A Control Architecture for Quadruped Locomotion Over Rough Terrain
• High-Accuracy 3D Sensing for Mobile Manipulation: Improving Object Detection and Door Opening
• Learning 3-D Object Orientation from Images
• Learning Sound Location from a Single Microphone
• Reactive Grasping Using Optical Proximity Sensors
• Stereo Vision and Terrain Modeling for Quadruped Robots
• Task-Space Trajectories via Cubic Spline Optimization
• A Probabilistic Approach to Mixed Open-loop and Closed-loop Control, with Application to Extreme Autonomous Driving
• Learning to grasp objects with multiple contact points
• Multi-Camera Object Detection for Robotics
• Autonomous Operation of Novel Elevators for Robot Navigation
• Autonomous Sign Reading for Semantic Mapping
• Grasping with Application to an Autonomous Checkout Robot
• A Low-cost Compliant 7-DOF Robotic Manipulator
• ROS: an open-source Robot Operating System
• Link Analysis, Eigenvectors and Stability
• Depth Estimation using Monocular and Stereo Cues
• Exponential Family Sparse Coding with Applications to Self-taught Learning
• A sparse sampling algorithm for near-optimal planning in large Markov decision processes
• 3-D Depth Reconstruction from a Single Still Image
• Robotic Grasping of Novel Objects using Vision
• Autonomous Helicopter Aerobatics through Apprenticeship Learning
• Apprenticeship Learning for Motion Planning with Application to Parking Lot Navigation
• Joint calibration of multiple sensors
• Scalable Learning for Object Detection with GPU Hardware
• Grasping Novel Objects with Depth Segmentation
• Low-cost Accelerometers for Robotic Manipulator Perception
• Have we met? MDP Based Speaker ID for Robot Dialogue
• Autonomous inverted helicopter flight via reinforcement learning
• Learning to Grasp Novel Objects using Vision
• Autonomous Autorotation of an RC Helicopter
• Automatic Single-Image 3d Reconstructions of Indoor Manhattan World Scenes
• A Vision-based System for Grasping Novel Objects in Cluttered Environments
• Latent Dirichlet Allocation (Extended Version)
• Learning Factor Graphs in Polynomial Time and Sample Complexity
• An Experimental and Theoretical Comparison of Model Selection Methods
• On Discriminative vs. Generative Classifiers: A comparison of logistic regression and Naive Bayes
• Latent Dirichlet Allocation
• On Spectral Clustering: Analysis and an algorithm
• Distance metric learning, with application to clustering with side-information
• Policy search by dynamic programming
• Classification with Hybrid Generative/Discriminative Models
• Learning first-order Markov models for control
• Learning syntactic patterns for automatic hypernym discovery
• Online Bounds for Bayesian Algorithms
• Stable adaptive control with online learning
• Fast Gaussian Process Regression using KD-Trees
• Learning vehicular dynamics, with application to modeling helicopters
• On Local Rewards and Scaling Distributed Reinforcement Learning
• Learning Depth from Single Monocular Images
• Transfer learning for text classification
• Hierarchical Apprenticeship Learning, with Application to Quadruped Locomotion
• Efficient multiple hyperparameter learning for log-linear models
• Sparse deep belief net model for visual area V2
• Unsupervised feature learning for audio classification using convolutional deep belief networks
• Measuring Invariances in Deep Networks
• Energy Disaggregation via Discriminative Sparse Coding
• Tiled convolutional neural networks
• Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection
• ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning
• Selecting Receptive Fields in Deep Networks
• Sparse Filtering
• Unsupervised learning models of primary cortical receptive fields and receptive field plasticity
• Policy Search via Density Estimation
• Approximate Planning in Large POMDPs via Reusable Trajectories
• Approximate inference algorithms for two-layer Bayesian networks
• An Analysis of Single-Layer Networks in Unsupervised Feature Learning
• Learning Continuous Phrase Representations and Syntactic Parsing with Recursive Neural Networks
• A Probabilistic Model for SemanticWord Vectors
• On Random Weights and Unsupervised Feature Learning
• Theorem 2.2: Near-optimality of optimal circular input for full convolution
• Applying Online-search to Reinforcement Learning
• From Uncertainty to Belief: Inferring the Specification Within
• Make3D: Learning 3D Scene Structure from a Single Still Image
• Approximate planning in large POMDPs via reusable trajectories
• Learning to Open New Doors
• Discriminative Training of Kalman Filters
• Learning Omnidirectional Path Following Using Dimensionality Reduction
• Policy Search via the Signed Derivative
• Policy invariance under reward transformations: Theory and application to reward shaping
• Stable Algorithms for Link Analysis
• Contextual Search and Name Disambiguation in Email Using Graphs
• Data-Intensive Question Answering
• PEGASUS: A policy search method for large MDPs and POMDPs
• Learning Factor Graphs in Polynomial Time and Sample Complexity
• Shift-Invariant Sparse Coding for Audio Classification
• An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering

Publications

• Metastable Chimera States in Community-Structured Oscillator Networks
• An attempt to formalise a non-trivial benchmark problem in common sense reasoning
• Modeling the Neural Basis of Cognitive Integration and Consciousness
• High-Level Robot Control Through Logic
• How Well Do Oscillator Models Capture the Behaviour of Biological Neurons?
• STDP Produces Robust Oscillatory Architectures That Exhibit Precise Collective Synchronization
• A Circumscriptive Calculus of Events
• Perception as Abduction: Turning Sensor Data Into Meaningful Representation
• A Spiking Neuron Model of Cortical Broadcast and Competition
• Supplementary Note on "A Spiking Neuron Model of Cortical Broadcast and Competition"
• Representing Continuous Change in The Event Calculus
• Reasoning about Discontinuities in the Event Calculus
• High-Level Robot Control Through Logic
• Event Calculus Planning Revisited
• The Event Calculus Explained
• Using Reactive Rules to Guide a Forward-Chaining Planner
• What Sort of Computation Mediates Best between Perception and Action?
• The Partial Information Decomposition of Generative Neural Network Models
• Evolutionary Automata
• Prediction is Deduction but Explanation is Abduction
• Explanation in the Situation Calculus
• Indirect and Conditional Sensing in the Event Calculus
• GPU-based Fast Parameter Optimization for Phenomenological Spiking Neural Models
• Conditional Neural Processes
• From Images to Bodies: Modelling and Exploiting Spatial Occlusion and Motion Parallax
• Training a Spiking Neural Network to Control a 4-DoF Robotic Arm based on Spike Timing-Dependent Plasticity
• Accelerated Simulation of Spiking Neural Networks Using GPUs
• Incrementality and Logic Programming
• The role of cortical oscillations in a spiking neural network model of the basal ganglia
• Continual Reinforcement Learning with Complex Synapses
• A Logical Account of Perception Incorporating Feedback and Expectation
• A Logic-Based Formulation of Active Visual Perception
• Cognition, Action Selection, and Inner Rehearsal
• Folk Psychology and Naïve Physics
• An Investigation of the Dynamical Transitions in Harmonically Driven Random Networks of Firing-Rate Neurons
• A computational model of a global neuronal workspace with stochastic connections
• An abductive event calculus planner
• The Ramification Problem in the Event Calculus
• Noise and the Common Sense Informatic Situation for a Mobile Robot
• Noise, Non-Determinism and Spatial Uncertainty
• Robotics and the Common Sense Informatic Situation
• Hypothesising Object Relations from Image Transitions
• SCAN: Learning Hierarchical Compositional Visual Concepts
• Reinventing Shakey
• Consciousness, Emotion, and Imagination: A Brain-Inspired Architecture for Cognitive Robotics
• Towards a Computational Account of Reflexive Consciousness
• Applying global workspace theory to the frame problem
• A cognitive architecture that combines internal simulation with a global workspace
• Global Access, Embodiment, and the Conscious Subject
• Satori Before Singularity
• The Dynamical Complexity of Small-World Networks of Spiking Neurons
• The Brain's Connective Core and its Role in Animal Cognition
• Event Calculus Planning Through Satisfiability
• Default Reasoning about Spatial Occupancy
• Does Plasticity Promote Criticality?
• Metastability and chimera states in modular delay and pulse-coupled oscillator networks
• Hierarchical Clustering Identifies Hub Nodes in a Model of Resting-State Brain Activity

• On the geometry and cohomology of some simple Shimura varieties
• The Consistency of the Axiom of Choice and of the Generalized Continuum-Hypothesis
• An Investigation of the Laws of Thought
• Six Books of the Elements of Euclid
• On sets of integers containing k elements in arithmetic progression
• Ars magna or The rules of algebra
• The Aryabhatiya Of Aryabhata: An Ancient Indian Work On Mathematics And Astronomy
• Categories for the Working Mathematician
• On the evolution of random graphs
• On convergence and growth of partial sums of Fourier series
• General Theory of Natural Equivalences
• Higher Topos Theory
• Homological Algebra
• Solvability of groups of odd order
• Automorphic Forms on GL(2)
• On formally undecidable propositions of Principia. Mathematica and related systems
• Nine Chapters on the Mathematical Art
• La conjecture deWeil : I
• The Independence of the Continuum Hypothesis
• Principia Mathematica
• Surya Siddhanta
• The Principia: Mathematical Principles of Natural Philosophy
• The Theory of Algebraic Number Fields
• Systems of Logic Based on Ordinals
• Modular elliptic curves and Fermat's Last Theorem
• Begriffsschrift: a formula language, modeled on that of arithmetic, of pure thought
• Winning Ways for Your Mathematical Plays: Volume 1
• Equilibrium points in n-person games
• Winning Ways for Your Mathematical Plays: Volume 4
• How long is the coast of Britain? Statistical self-similarity and fractional dimension
• The method of fluxions and infinite series: with its application to the geometry of curve-lines
• The Schoolmaster's Assistant, Being a Compendium of Arithmetic both Practical and Theoretical
• Theory of Games and Economic Behavior
• Kiselev's Geometry: Planimetry
• A Course of Pure Mathematics
• Calculus, Volume 2: Multi-Variable Calculus and Linear Algebra, with Applications to Differential Equations and Probability
• Calculus, Volume 1: One-Variable Calculus, with an Introduction to Linear Algebra
• Naive set theory
• Set Theory An Introduction To Independence Proofs
• Topology from the Differentiable Viewpoint
• Foundations of Differential Geometry (Volume 1)
• Foundations of Differential Geometry (Volume 2)
• General Topology
• Hodge Theory and Complex Algebraic Geometry II
• Hodge Theory and Complex Algebraic Geometry I