Publications

2021

      PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception (web) (bibtex)

      Aviv Netanyahu*, Tianmin Shu*, Boris Katz, Andrei Barbu, Joshua B. Tenenbaum:
      35th AAAI Conference on Artificial Intelligence (AAAI)
      #social perception, #theory of mind, #bayesian inverse planning

2020

      A Morphable Face Albedo Model (pdf) (bibtex)

      William A.P Smith, Alassane Seck, Hannah Dee, Bernard Tiddeman, Josh Tenenbaum, Bernhard Egger:
      Conference on Computer Vision and Pattern Recognition (CVPR)
      #3d morphable model, #inverse rendering

      Adventures in Flatland: Perceiving Social Interactions Under Physical Dynamics (pdf) (bibtex)

      Tianmin Shu, Marta Kryven, Tomer D. Ullman, Joshua B. Tenenbaum:
      Proceedings of the 42nd Annual Virtual Meeting of the Cognitive Science Society
      #social perception, #theory of mind, #intuitive physics, #bayesian inverse planning, #hierarchical planning

      Few-shot Bayesian imitation learning with logical program policies (pdf) (bibtex)

      Tom Silver, Kelsey Allen, Leslie Kaelbling, Josh Tenenbaum:
      AAAI
      #rl, #imitation learning, #program synthesis

      How many observations is one generic worth? (web) (bibtex)

      Tessler, M. H., Bridgers, S., & Tenenbaum, J. B.:
      Proceedings of the 42nd Annual Virtual Meeting of the Cognitive Science Society
      #language, #pragmatics, #generics, #pedagogy, #bayesian learning

      Inverse Rendering Best Explains Face Perception Under Extreme Illuminations (bibtex)

      Bernhard Egger, Max Siegel, Riya Arora, Amir Arsalan Soltani, Ilker Yildirm, Josh Tenenbaum:
      Proceedings of the 42nd Annual Virtual Meeting of the Cognitive Science Society
      #3d morphable model, #inverse rendering

      Perspective Plane Program Induction from a Single Image (web) (bibtex)

      Yikai Li*, Jiayuan Mao*, Xiuming Zhang, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu:
      Conference on Computer Vision and Pattern Recognition (CVPR)
      #inverse graphics, #image manipulation

      Program Synthesis with Pragmatic Communication (web) (bibtex)

      Yewen Pu, Kevin Ellis, Marta Kryven, Josh Tenenbaum, Armando Solar-Lezama:
      2nd ICML 2020 Workshop on Human in the Loop Learning
      #communication, #pragmatics, #program induction

2019

      A Computational Model for Combinatorial Generalization in Physical Perception from Sound (pdf) (bibtex)

      Yunyun Wang, Chuang Gan, Max H. Siegel, Zhoutong Zhang, Jiajun Wu, Joshua B. Tenenbaum:
      Conference on Cognitive Computational Neuroscience (CCN)
      #auditory scene analysis, #deep learning, #compositionality

      An Integrative Computational Architecture for Object-Driven Cortex (web) (bibtex)

      Ilker Yildirim, Jiajun Wu, Nancy Kanwisher, Joshua B. Tenenbaum:
      Current Opinion in Neurobiology (CONEUR)
      #computational neuroscience, #object representation

      Combining Physical Simulators and Object-Based Networks for Control (web) (bibtex)

      Anurag Ajay, Maria Bauza, Jiajun Wu, Nima Fazeli, Joshua B. Tenenbaum, Alberto Rodriguez, Leslie P. Kaelbling:
      IEEE International Conference on Robotics and Automation (ICRA)
      #dynamics modeling, #deep learning, #robotics

      DensePhysNet: Learning Dense Physical Object Representations via Multi-step Dynamic Interactions (web) (bibtex)

      Zhenjia Xu, Jiajun Wu, Andy Zeng, Joshua B. Tenenbaum, Shuran Song:
      Robotics: Science and Systems (RSS)
      #deep learning, #robotics, #intuitive physics

      Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, Fluids (web) (bibtex)

      Yunzhu Li, Jiajun Wu, Russ Tedrake, Joshua B. Tenenbaum, Antonio Torralba:
      International Conference on Learning Representations (ICLR)
      #dynamics predicting, #planning and control

      Modeling expertise with neurally-guided Bayesian program induction (web) (bibtex)

      C. Wong, K. Ellis, M. Sable-Meyer, J. Tenenbaum:
      Proceedings of the 41st Annual Meeting of the Cognitive Science Society
      #expertise, #program induction

      Neurally-Guided Structure Inference (web) (bibtex)

      Sidi Lu, Jiayuan Mao, Joshua B. Tenenbaum, Jiajun Wu:
      International Conference on Machine Learning (ICML)
      #machine learning, #compositionality

      Propagation Networks for Model-Based Control Under Partial Observation (web) (bibtex)

      Yunzhu Li, Jiajun Wu, Jun-Yan Zhu, Antonio Torralba, Joshua B. Tenenbaum, Russ Tedrake:
      IEEE International Conference on Robotics and Automation (ICRA)
      #dynamics modeling, #deep learning, #robotics

      Reasoning About Physical Interactions with Object-Oriented Prediction and Planning (web) (bibtex)

      Michael Janner, Sergey Levine, William T. Freeman, Joshua B. Tenenbaum, Chelsea Finn, Jiajun Wu:
      International Conference on Learning Representations (ICLR)
      #computer vision, #dynamics prediction, #planning

      See, Feel, Act: Hierarchical Learning for Complex Manipulation Skills with Multi-sensory Fusion (web) (bibtex)

      Nima Fazeli, Miquel Oller, Jiajun Wu, Zheng Wu, Joshua B. Tenenbaum, Alberto Rodriguez:
      Science Robotics
      #robotics, #deep learning, #dynamics modeling, #manipulation

      Stochastic Prediction of Multi-Agent Interactions from Partial Observations (web) (bibtex)

      Chen Sun, Per Karlsson, Jiajun Wu, Joshua B. Tenenbaum, Kevin Murphy:
      International Conference on Learning Representations (ICLR)
      #dynamics prediction

      The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, Sentences From Natural Supervision (web) (bibtex)

      Jiayuan Mao, Chuang Gan, Pushmeet Kohli, Joshua B. Tenenbaum, Jiajun Wu:
      International Conference on Learning Representations (ICLR)
      #computer vision, #visual reasoning, #neuro-symbolic algorithms

      Unsupervised Discovery of Parts, Structure, and Dynamics (web) (bibtex)

      Zhenjia Xu, Zhijian Liu, Chen Sun, Kevin Murphy, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu:
      International Conference on Learning Representations (ICLR)
      #dynamics prediction, #computer vision

      Visual Concept-Metaconcept Learning (web) (bibtex)

      Chi Han*, Jiayuan Mao*, Chuang Gan, Joshua B. Tenenbaum, Jiajun Wu:
      Advances in Neural Information Processing Systems
      #language, #concept learning

2018

      3D Interpreter Networks for Viewer-Centered Wireframe Modeling (web) (bibtex)

      Jiajun Wu, Tianfan Xue, Joseph J. Lim, Yuandong Tian, Joshua B. Tenenbaum, Antonio Torralba, William T. Freeman:
      International Journal of Computer Vision (IJCV)
      #3d vision, #deep learning

      3D Shape Perception from Monocular Vision, Touch, and Shape Priors (web) (bibtex)

      Shaoxiong Wang, Jiajun Wu, Xingyuan Sun, Wenzhen Yuan, William T. Freeman, Joshua B. Tenenbaum, Edward H. Adelson:
      IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
      #3d vision, #multi-modal learning, #deep learning

      A critical period for second language acquisition: Evidence from 2/3 million English speakers. (pdf) (bibtex)

      J. K. Hartshorne, J. B. Tenenbaum, S. Pinker:
      Cognition
      #language

      Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing (web) (bibtex)

      Anurag Ajay, Jiajun Wu, Nima Fazeli, Maria Bauza, Leslie P. Kaelbling, Joshua B. Tenenbaum, Alberto Rodriguez:
      IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
      #dynamics modeling, #deep learning, #robotics

      Learning Shape Priors for Single-View 3D Completion and Reconstruction (web) (bibtex)

      Jiajun Wu, Chengkai Zhang, Xiuming Zhang, Zhoutong Zhang, William T. Freeman, Joshua B. Tenenbaum:
      European Conference on Computer Vision (ECCV)
      #3d vision, #deep learning

      Learning to Reconstruct Shapes from Unseen Classes (web) (bibtex)

      Xiuming Zhang, Zhoutong Zhang, Chengkai Zhang, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu:
      Advances in Neural Information Processing Systems (NeurIPS)
      #3d vision, #deep learning

      Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding (web) (bibtex)

      Kexin Yi, Jiajun Wu, Chuang Gan, Antonio Torralba, Pushmeet Kohli, Joshua B. Tenenbaum:
      Advances in Neural Information Processing Systems (NeurIPS)
      #visual reasoning, #deep learning, #scene understanding

      Neurocomputational Modeling of Human Physical Scene Understanding (pdf) (bibtex)

      Ilker Yildirim, Kevin Smith, Mario Belledonne, Jiajun Wu, Joshua B. Tenenbaum:
      Conference on Cognitive Computational Neuroscience (CCN)
      #intuitive physics, #deep learning, #scene understanding

      Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling (web) (bibtex)

      Xingyuan Sun, Jiajun Wu, Xiuming Zhang, Zhoutong Zhang, Chengkai Zhang, Tianfan Xue, Joshua B. Tenenbaum, William T. Freeman:
      IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
      #3d vision, #deep learning

      Unsupervised Learning of Latent Physical Properties Using Perception-Prediction Networks (web) (bibtex)

      David Zheng, Vinson Luo, Jiajun Wu, Joshua B. Tenenbaum:
      Conference on Uncertainty in Artificial Intelligence (UAI)
      #intuitive physics, #scene understanding, #graph networks

      Visual Object Networks: Image Generation with Disentangled 3D Representations (web) (bibtex)

      Jun-Yan Zhu, Zhoutong Zhang, Chengkai Zhang, Jiajun Wu, Antonio Torralba, Joshua B. Tenenbaum, William T. Freeman:
      Advances in Neural Information Processing Systems (NeurIPS)
      #3d vision, #deep learning

2017

2016

      A Comparative Evaluation of Approximate Probabilistic Simulation and Deep Neural Networks as Accounts of Human Physical Scene Understanding (web) (bibtex)

      Renqiao Zhang, Jiajun Wu, Chengkai Zhang, William T. Freeman, Joshua B. Tenenbaum:
      Proceedings of the 38th Annual Conference of the Cognitive Science Society
      #intuitive physics, #simulation, #deep learning, #scene understanding

      Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation (web) (bibtex)

      Tejas D Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Josh Tenenbaum:
      Advances in Neural Information Processing Systems (NIPS)
      #reinforcement learning, #hierarchical modeling, #deep learning

      Implicit measurement of motivated causal attribution (pdf) (bibtex)

      Laura Niemi, Joshua Hartshorne, Tobias Gerstenberg, Liane Young:
      Proceedings of the 38th Annual Conference of the Cognitive Science Society
      #morality, #causality, #language

      Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling (web) (bibtex)

      Jiajun Wu, Chengkai Zhang, Tianfan Xue, William T. Freeman, Joshua B. Tenenbaum:
      Advances in Neural Information Processing Systems (NIPS)
      #simulation, #deep learning, #generative adversarial learning, #3d vision

      Natural science: Active learning in dynamic physical microworlds (pdf) (bibtex)

      Neil Bramley, Tobias Gerstenberg, Joshua B. Tenenbaum:
      Proceedings of the 38th Annual Conference of the Cognitive Science Society
      #causality, #learning, #intuitive physics

      Plans, habits, and theory of mind (web) (bibtex)

      Sam Gershman*, Tobias Gerstenberg*, Chris Baker, Fiery Cushman:
      PLoS ONE
      #planning, #theory of mind, #habit

      Understanding “almost”: Empirical and computational studies of near misses (pdf) (bibtex)

      Tobias Gerstenberg, Joshua B. Tenenbaum:
      Proceedings of the 38th Annual Conference of the Cognitive Science Society
      #counterfactuals, #causality, #intuitive physics, #language, #almost

2015

      A difference-making framework for intuitive judgments of responsibility (pdf) (bibtex)

      David Lagnado, Tobias Gerstenberg:
      Oxford Studies in Agency and Responsibility
      #responsibility, #causality, #counterfactuals

      Assessing the perceived predictability of functions (pdf) (bibtex)

      Schulz E., Tenenbaum J.B., Reshef D.N., Speekenbrink M., Gershman, S.J.:
      Proceedings of the 37th Annual Conference of the Cognitive Science Society.
      #function learning, #predictability, #smoothness, #gaussian processes

      Causal conceptions in social explanation and moral evaluation: A historical tour (pdf) (bibtex)

      Mark Alicke, David Mandel, Denis Hilton, Tobias Gerstenberg, David Lagnado:
      Perspectives on Psychological Science
      #causality, #attribution, #counterfactuals, #theory of mind

      Children’s understanding of the costs and rewards underlying rational action (web) (bibtex)

      Jara-Ettinger J., Gweon H., Tenenbaum J.B., Schulz E.:
      Cognition
      #social cognition, #theory of mind

      Computational rationality: a converging paradigm for intelligence in brains, minds, and machines (pdf) (bibtex)

      S.J. Gershman, E.J. Horvitz, J.B. Tenenbaum:
      Science
      #decision making, #reinforcement learning, #hypothesis sampling

      Concepts in a probabilistic language of thought (pdf) (bibtex)

      Noah Goodman, Joshua Tenenbaum, Tobias Gerstenberg:
      The Conceptual Mind: New Directions in the Study of Concepts
      #concepts, #representation, #learning, #causality, #intuitive physics, #intuitive psychology

      Deep Convolutional Inverse Graphics Network (web) (bibtex)

      Tejas D Kulkarni, William F Whitney, Pushmeet Kohli, Josh Tenenbaum:
      Advances in Neural Information Processing Systems (NIPS)
      #inverse vision, #deep learning, #disentangled representation,

      Discovering hierarchical motion structure (pdf) (bibtex)

      S.J. Gershman, J.B. Tenenbaum, F. Jaekel:
      Vision Research
      #motion perception; structure learning

      Efficient analysis-by-synthesis in vision: A computational framework, behavioral tests, and modeling neuronal representations (pdf) (bibtex)

      Ilker Yildirim, Tejas D. Kulkarni, Winrich A. Freiwald, Joshua B. Tenenbaum:
      Proceedings of the Thirty-Seventh Annual Conference of the Cognitive Science Society
      #analysis-by-synthesis, #psychophysics, #neural modeling, #face perception, #macaque face patches

      Go fishing! Responsibility judgments when cooperation breaks down (pdf) (bibtex)

      Kelsey Allen, Julian Jara-Ettinger, Tobias Gerstenberg, Max Kleiman-Weiner, Joshua Tenenbaum:
      Proceedings of the 37th Annual Conference of the Cognitive Science Society
      #responsibility, #cooperation, #counterfactuals, #causality, #social cognition

      How, whether, why: Causal judgments as counterfactual contrasts (pdf) (bibtex)

      Tobias Gerstenberg, Noah Goodman, David Lagnado, Joshua Tenenbaum:
      Proceedings of the 37th Annual Conference of the Cognitive Science Society
      #causality, #counterfactuals, #intuitive physics

      Phrase similarity in humans and machines (pdf) (bibtex)

      S.J. Gershman, J.B. Tenenbaum:
      Proceedings of the 37th Annual Conference of the Cognitive Science Society.
      #similarity; semantics; neural networks

      Picture : A Probabilistic Programming Language for Scene Perception (pdf) (doi) (bibtex)

      Tejas D Kulkarni, Pushmeet Kohli, Joshua B Tenenbaum, Vikash Mansinghka:
      Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
      #analysis-by-synthesis, #inference, #deep learning, #inverse vision, #3d vision, #probabilistic programming

      Responsibility judgments in voting scenarios (pdf) (bibtex)

      Tobias Gerstenberg, Joseph Halpern, Joshua Tenenbaum:
      Proceedings of the 37th Annual Conference of the Cognitive Science Society
      #responsibility, #causality, #counterfactuals

      Risk and Regret of Hierarchical Bayesian Learners (pdf) (bibtex)

      Jonathan H. Huggins, Joshua B. Tenenbaum:
      Proceedings of the 32nd International Conference on Machine Learning
      #learning theory, #hierarchical modeling

      Structure and flexibility in Bayesian models of cognition (pdf) (bibtex)

      Austerweil, J.L., S.J. Gershman, J.B. Tenenbaum, T.L. Griffiths:
      Oxford Handbook of Computational and Mathematical Psychology
      #bayesian nonparametrics; structure learning

      The causes and consequences explicit in verbs (pdf) (bibtex)

      J. K. Hartshorne, T. J. O’Donnell, J. B. Tenenbaum:
      Language, Cognition, and Neuroscience
      #language, #common sense

      Toddlers’ inferences about costs and culpability (bibtex)

      Jara-Ettinger J., Tenenbaum J.B., Schulz E.:
      Psychological Science
      #social cognition, #theory of mind

2014

      Causal supersession (pdf) (bibtex)

      J. F. Kominsky, J. Phillips, J. Knobe, T. Gerstenberg, D. A. Lagnado:
      Proceedings of the 36th Annual Conference of the Cognitive Science Society
      #counterfactuals, #causality, #morality

      From counterfactual simulation to causal judgment (pdf) (bibtex)

      T. Gerstenberg, N. D. Goodman, D. A. Lagnado, J. B. Tenenbaum:
      Proceedings of the 36th Annual Conference of the Cognitive Science Society
      #causality, #counterfactuals, #simulation, #intuitive physics, #attribution

      The order of things: Inferring causal structure from temporal patterns (pdf) (bibtex)

      N. R. Bramley, T. Gerstenberg, D. A. Lagnado:
      Proceedings of the 36th Annual Conference of the Cognitive Science Society
      #causality, #inference, #learning, #bayesian modeling

      Wins above replacement: Responsibility attributions as counterfactual replacements (pdf) (bibtex)

      T. Gerstenberg, T. D. Ullman, M. Kleiman-Weiner, D. A. Lagnado, J. B. Tenenbaum:
      Proceedings of the 36th Annual Conference of the Cognitive Science Society
      #responsibility, #attribution, #counterfactuals, #causality, #bayesian modeling, #theory of mind

2013

      Consistent physics underlying ballistic motion prediction (pdf) (bibtex)

      Smith KA, Battaglia PW, Vul E:
      Proceedings of the 35th Annual Conference of the Cognitive Science Society
      #intuitive physics, #bayesian model

      Back on track: Backtracking in counterfactual reasoning (pdf) (bibtex)

      T. Gerstenberg, C. Bechlivanidis, D.A. Lagnado:
      Proceedings of the 35th Annual Conference of the Cognitive Science Society
      #counterfactuals, #causality, #inference, #backtracking

      Bayesian vector analysis and the perception of hierarchical motion (pdf) (bibtex)

      S.J. Gershman, F.J. Jaekel, J.B. Tenenbaum:
      Proceedings of the Thirty-Fifth Annual Conference of the Cognitive Science Society
      #vision, #motion perception

      Compositional policy priors (pdf) (bibtex)

      D. Wingate, C. Diuk, T. O’Donnell, J.B. Tenenbaum, S.J. Gershman:
      MIT CSAIL Technical Report 2013-007
      #reinforcement learning, #grammar induction

      Knowledge and implicature: Modeling language understanding as social cognition (pdf) (bibtex)

      N. D. Goodman, A. Stuhlmueller:
      Topics in Cognitive Science
      #language, #pragmatics

      Not so innocent: Reasoning about costs, competence, and culpability in very early childhood. (pdf) (bibtex)

      J. Jara-Ettinger, J. Tenenbaum, L. Schulz.:
      Proceedings of the 35th Annual Conference of the Cognitive Science Society.
      #social cognition, #theory of mind, #cognitive development, #morality

      Reasoning about Reasoning by Nested Conditioning: Modeling Theory of Mind with Probabilistic Programs (pdf) (bibtex)

      A. Stuhlmueller, N. D. Goodman:
      Journal of Cognitive Systems Research
      #theory of mind, #probabilistic programming

      Structure discovery in nonparametric regression through compositional kernel search (pdf) (bibtex)

      D. Duvenaud, J. R. Lloyd, R. B. Grosse, J. B. Tenenbaum, Z. Ghahramani:
      International Conference on Machine Learning
      #structure discovery, #unsupervised learning, #bayesian model

      The mentalistic basis of core social cognition: Experiments in preverbal infants and a computational model (web) (bibtex)

      J. K. Hamlin, T. D. Ullman, J. B. Tenenbaum, N. D. Goodman, C. L. Baker:
      Developmental Science
      #morality, #infants, #goal inference, #theory of mind, #inverse planning

2012

      Theory learning as stochastic search in the language of thought (pdf) (bibtex)

      T. D. Ullman, N. D. Goodman and J. B. Tenenbaum:
      Cognitive Development
      #children, #theory learning, #intuitive theories, #mcmc, #search

      A Dynamic Programming Algorithm for Inference in Recursive Probabilistic Programs (web) (bibtex)

      A. Stuhlmueller, N. D. Goodman:
      Second Statistical Relational AI workshop at UAI 2012 (StaRAI-12)
      #dynamic programming, #inference, #probabilistic programming

      Exploiting compositionality to explore a large space of model structures (pdf) (bibtex)

      R. B. Grosse, R. Salakhutdinov, W. T. Freeman, J. B. Tenenbaum:
      Proceedings of the 28th Conference on Uncertainty in AI (UAI)
      #structure discovery, #unsupervised learning, #bayesian model

      Finding fault: Causality and counterfactuals in group attributions (pdf) (bibtex)

      R. Zultan, T. Gerstenberg, D.A. Lagnado:
      Cognition
      #responsibility attribution, #counterfactuals, #causality, #groups

      Multistability and Perceptual Inference (pdf) (bibtex)

      S.J. Gershman, E. Vul, J.B. Tenenbaum:
      Neural Computation
      #vision, #mcmc

      Noisy Newtons: Unifying process and dependency accounts of causal attribution (pdf) (bibtex)

      T. Gerstenberg, N.D. Goodman, D.A. Lagnado, J.B. Tenenbaum:
      Proceedings of the 34th Annual Conference of the Cognitive Science Society
      #causality, #counterfactuals, #attribution, #intuitive physics

      Sticking to the evidence? A computational and behavioral case study of micro-theory change in the domain of magnetism (pdf) (bibtex)

      E. Bonawitz, T.D. Ullman, A. Gopnik, J. B. Tenenbaum:
      IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL)
      #children, #theory learning, #intuitive theories, #magnetism

      Towards common-sense reasoning via conditional simulation: Legacies of Turing in Artificial Intelligence (web) (bibtex)

      C. E. Freer, D. M. Roy, J. B. Tenenbaum:
      Turing’s Legacy (ASL Lecture Notes in Logic)
      #probabilistic programming, #artificial intelligence, #reasoning, #decision making, #structure learning

      When contributions make a difference: Explaining order effects in responsibility attributions (pdf) (bibtex)

      T. Gerstenberg, D.A. Lagnado:
      Psychonomic Bulletin & Review
      #responsibility attribution, #order effect, #counterfactuals, #causal chain, #causal reasoning, #judgment and decision making, #social cognition

      Why blame Bob? Probabilistic generative models, counterfactual reasoning, and blame attribution (pdf) (bibtex)

      J. McCoy, T. D. Ullman, A. Stuhlmueller, T. Gerstenberg, J. B. Tenenbaum:
      Proceedings of the Thirty-Fourth Annual Conference of the Cognitive Science Society
      #counterfactuals, #blame attribution, #probabilistic models, #causal reasoning

2011

      Internal physics models guide probabilistic judgments about object dynamics (pdf) (bibtex)

      Hamrick JB, Battaglia PW, Tenenbaum JB:
      33rd Annual Conference of the Cognitive Science Society
      #intuitive physics, #bayesian model

      Beyond outcomes: The influence of intentions and deception (pdf) (bibtex)

      S. Schaechtele, T. Gerstenberg, D.A. Lagnado:
      Proceedings of the 33rd Annual Conference of the Cognitive Science Society
      #intentions, #outcomes, #preferences, #deception, # punishment, #reward, #experimental games

      Blame the skilled (pdf) (bibtex)

      T. Gerstenberg, A. Ejova, D. A. Lagnado:
      Proceedings of the 33rd Annual Conference of the Cognitive Science Society
      #responsibility attribution, #counterfactual thinking, #control, #skil

      Inducing Probabilistic Programs by Bayesian Program Merging (web) (bibtex)

      I. Hwang, A. Stuhlmueller, N. D. Goodman:
      Technical Report. arXiv:1110.5667 [cs.AI]
      #probabilistic programming, #program induction

      Learning What is Where From Social Observations (pdf) (bibtex)

      J Jara-Ettinger, C. Baker, J. Tenenbaum:
      Proceedings of the 34th Annual Conference of the Cognitive Science Society
      #social cognition, #theory of mind

      Learning a theory of causality (pdf) (bibtex)

      N. D. Goodman, T. D. Ullman, and J. B. Tenenbaum:
      Psychological review
      #causality, #theory learning, #causal networks

      Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation (pdf) (bibtex)

      D. Wingate, A. Stuhlmueller, N. D. Goodman:
      Proceedings of the 14th international conference on Artificial Intelligence and Statistics
      #probabilistic programming, #mcmc, #inference

      Nonstandard Interpretations of Probabilistic Programs for Efficient Inference (pdf) (bibtex)

      D. Wingate, N. D. Goodman, A. Stuhlmueller, J. M. Siskind:
      Advances in Neural Information Processing Systems (NIPS) 24
      #probabilistic programming, #inference

      Ping Pong in Church: Productive use of concepts in human probabilistic inference (pdf) (bibtex)

      T. Gerstenberg, N.D. Goodman:
      Proceedings of the 34th Annual Conference of the Cognitive Science Society
      #inference, #reasoning, #causality, #language of thought, #probabilistic programming

      Rational order effects in responsibility attributions (pdf) (bibtex)

      T. Gerstenberg, D.A. Lagnado, M. Speekenbrink, C. Cheung:
      Proceedings of the 33rd Annual Conference of the Cognitive Science Society
      #responsibility attribution, #causal chain, #order effect

2010

      Beyond Boolean Logic: Exploring Representation Languages for Learning Complex Concepts (pdf) (bibtex)

      S. T. Piantadosi, N. D. Goodman, J. B. Tenenbaum:
      Proceedings of the 32nd Cognitive Science Conference
      #concept learning, #language

      Discovering structure by learning sparse graphs (pdf) (bibtex)

      B. M. Lake, J. B. Tenenbaum:
      Proceedings of the 32nd Cognitive Science Conference
      #structure discovery, #semantic cognition, #unsupervised learning

      Help or hinder: Bayesian models of social goal inference (pdf) (bibtex)

      T.D. Ullman, C.L. Baker, O. Macindoe, O. Evans, N.D. Goodman, J.B. Tenenbaum:
      Advances in Neural Information Processing Systems
      #morality

      Learning Structured Generative Concepts (pdf) (bibtex)

      A. Stuhlmueller, J. B. Tenenbaum, N. D. Goodman:
      Proceedings of the Thirty-Second Annual Conference of the Cognitive Science Society
      #concepts

      Smartlocks: Lock Acquisition Scheduling for Self-Aware Synchronization (pdf) (bibtex)

      J. Eastep, D. Wingate, M. D. Santambrogio, A. Agarwal:
      IEEE International Conference on Autonomic Computing and Communications
      #mutex, #reinforcement learning, #adaptive

      Spreading the blame: The allocation of responsibility amongst multiple agents (pdf) (bibtex)

      T. Gerstenberg, D.A. Lagnado:
      Cognition
      #collective responsibility, #attribution, #counterfactual reasoning, #causal models, #experimental games

      The dice are cast: The role of intended versus actual contributions in responsibility attribution (pdf) (bibtex)

      T. Gerstenberg, D.A. Lagnado, Y. Kareev:
      Proceedings of the 32nd Annual Conference of the Cognitive Science Society
      #responsibility, #attribution, #intentionality, #outcome bias, #experimental game

      Theory acquisition as stochastic search (pdf) (bibtex)

      T. D. Ullman, N. D. Goodman and J. B. Tenenbaum:
      Proceedings of the Thirty-Second Annual Conference of the Cognitive Science Society
      #theory learning, #intuitive theories, #development, #mcmc

      Variability, negative evidence, and the acquisition of verb argument constructions (pdf) (bibtex)

      A. F. Perfors, E. Wonnacott, J.B. Tenenbaum:
      Journal of Child Language
      #language

      When are probabilistic programs probably computationally tractable? (pdf) (bibtex)

      C. E. Freer, V. K. Mansinghka, D. M. Roy:
      NIPS Workshop on Monte Carlo Methods for Modern Applications
      #probabilistic programming

2009

      A Bayesian Sampling Approach to Exploration in Reinforcement Learning (pdf) (bibtex)

      J. Asmuth, L. Li, M. L. Littman, A. Nouri and D. Wingate:
      Uncertainty in Artificial Intelligence
      #bayesian, #sampling, #reinforcement learning

      Computable exchangeable sequences have computable de Finetti measures (pdf) (doi) (bibtex)

      C. E. Freer, D. M. Roy:
      Computability in Europe (CiE)
      #de finetti, #exchangeability, #computable probability theory, #probabilistic programming, #mutation

      Exact and approximate sampling by systematic stochastic search (pdf) (bibtex)

      V. K. Mansinghka, D. M. Roy, E. Jonas, J. B. Tenenbaum:
      AISTATS 2009
      #inference

      Learning a theory of causality (pdf) (bibtex)

      N. D. Goodman, T. D. Ullman, and J. B. Tenenbaum:
      Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society
      #causality, #theory learning, #causal networks

      Structured statistical models of inductive reasoning (pdf) (bibtex)

      C. Kemp, J. B. Tenenbaum:
      Psychological Review
      #inductive reasoning

      Theory-based causal induction (pdf) (bibtex)

      T. L. Griffiths, J. B. Tenenbaum:
      Psychological Review
      #causality

      Using speakers’ referential intentions to model early cross-situational word learning (pdf) (bibtex)

      M. C. Frank, N. D. Goodman, J. B. Tenenbaum:
      Psychological Science XX
      #language

2008

      A Bayesian framework for cross-situational word-learning (pdf) (bibtex)

      M. C. Frank, N. D. Goodman, J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 20
      #language

      A rational analysis of rule-based concept learning (pdf) (bibtex)

      N. D. Goodman, J. B. Tenenbaum, J. Feldman, T. L. Griffiths:
      Cognitive Science
      #concepts, #language of thought

      Bayesian models of cognition (pdf) (bibtex)

      T. L. Griffiths, C. Kemp, J. B. Tenenbaum:
      Cambridge Handbook of Computational Cognitive Modeling
      #chapter

      Church: a language for generative models (pdf) (bibtex)

      N. D. Goodman, V. K. Mansinghka, D. M. Roy, K. Bonawitz, J. B. Tenenbaum:
      Uncertainty in Artificial Intelligence 2008
      #church, #probabilistic programming, #generative models

      Inductive reasoning about causally transmitted properties (pdf) (bibtex)

      P. Shafto, C. Kemp, E. R. Baraff, J. Coley, J. B. Tenenbaum:
      Cognition
      #property induction, #inductive reasoning

      Learning and using relational theories (pdf) (bibtex)

      C. Kemp, N. D. Goodman, J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 20
      #theories, #language of thought

      The discovery of structural form (pdf) (bibtex)

      C. Kemp, J. B. Tenenbaum:
      Proceedings of the National Academy of Sciences
      #cognitive development, #structure discovery, #unsupervised learning

      Theory-based social goal inference (pdf) (bibtex)

      C.L. Baker, N.D. Goodman, J.B. Tenenbaum:
      Proceedings of the Thirtieth Annual Conference of the Cognitive Science Society
      #social cognition, #theory of mind, #action understanding, #goal inference, #inverse planning

2007

      A rational analysis of rule-based concept learning (pdf) (bibtex)

      N. D. Goodman, T. L. Griffiths, J. Feldman, J. B. Tenenbaum:
      Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society
      #concepts, #categorization

      AClass: An online algorithm for generative classification (pdf) (bibtex)

      V. K. Mansinghka, D. M. Roy, R. Rifkin, J. B. Tenenbaum:
      Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS07)
      #classification, #dirichlet process mixture, #particle filter

      Bayesian networks, Bayesian learning, and cognitive development (pdf) (bibtex)

      A. Gopnik, J. B. Tenenbaum:
      Developmental Science 10

      Causal inference in multisensory perception (web) (bibtex)

      K. P. Kording, U. Beierholm, W. J. Ma, S. Quartz, J. B. Tenenbaum, L. Shams:
      PLoS ONE

      Causal inference in sensorimotor integration. (pdf) (bibtex)

      K. Kording, J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 19

      Combining causal and similarity-based reasoning (pdf) (bibtex)

      C. Kemp, P. Shafto, A. Berke, J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 19

      Discovering syntactic hierarchies (pdf) (bibtex)

      V. Savova, D. M. Roy, L. Schmidt, J. B. Tenenbaum:
      Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society
      #annotated hierarchies, #stochastic blockmodels

      From mere coincidences to meaningful discoveries (pdf) (bibtex)

      T. L. Griffiths, J. B. Tenenbaum:
      Cognition 103

      Goal inference as inverse planning (pdf) (bibtex)

      C. L. Baker, J. B. Tenenbaum, R. Saxe:
      Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society
      #social cognition

      Intuitive theories as grammars for causal inference (pdf) (bibtex)

      J. B. Tenenbaum, T. L. Griffiths, S. Niyogi:
      Causal learning: Psychology, philosophy, and computation.
      #causality

      Learning annotated hierarchies from relational data (pdf) (bibtex)

      D. M. Roy, C. Kemp, V. K. Mansinghka, J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 19
      #stochastic blockmodels, #annotated hierarchies, #hierachical

      Learning causal schemata (pdf) (bibtex)

      C. Kemp, N. D. Goodman, J. B. Tenenbaum:
      Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society

      Learning grounded causal models (pdf) (bibtex)

      N. D. Goodman, V. K. Mansignhka, J. B. Tenenbaum:
      Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society

      Learning overhypotheses with hierarchical Bayesian models (pdf) (bibtex)

      C. Kemp, A. Perfors, J. B. Tenenbaum:
      Developmental Science 10

      Modeling human performance in statistical word segmentation (bibtex)

      M. Frank, S. Goldwater, T. L. Griffiths, V. K. Mansinghka, J. B. Tenenbaum:
      Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society

      Multiple timescales and uncertainty in motor adaptation. (pdf) (bibtex)

      K. Kording, J. B. Tenenbaum, R. Shadmehr:
      Advances in Neural Information Processing Systems 19

      Parametric embedding for class visualization (pdf) (bibtex)

      T. Iwata, K. Saito, N. Ueda, S. Stromsten, T. L. Griffiths, J. B. Tenenbaum:
      Neural Computation 19

      Sensitivity to sampling in Bayesian word learning (pdf) (bibtex)

      F. Xu, J. B. Tenenbaum:
      Developmental Science 10

      The dynamics of memory are a consequence of optimal adaptation to a changing body (pdf) (bibtex)

      K. P. Kording, J. B. Tenenbaum, R. Shadmehr:
      Nature Neuroscience 10

      The role of causality in judgment under uncertainty (pdf) (bibtex)

      T. R. Krynski, J. B. Tenenbaum:
      Journal of Experimental Psychology: General 136

      Theory-based Bayesian models of inductive reasoning (pdf) (bibtex)

      J. B. Tenenbaum, C. Kemp, P. Shafto:
      Inductive reasoning.

      Topics in semantic representation (pdf) (bibtex)

      T. L. Griffiths, M. Steyvers, J. B. Tenenbaum:
      Psychological Review 114

      Two proposals for causal grammars (pdf) (bibtex)

      T. L. Griffiths, J. B. Tenenbaum:
      Causal learning: Psychology, philosophy, and computation.

      Word learning as Bayesian inference (pdf) (bibtex)

      F. Xu, J. B. Tenenbaum:
      Psychological Review 114

2006

      Bayesian models of human action understanding (pdf) (bibtex)

      C. L. Baker, J. B. Tenenbaum, R. Saxe:
      Advances in Neural Information Processing Systems 18
      #social cognition

      Intuitive theories of mind: A rational approach to false belief (pdf) (bibtex)

      N. D. Goodman, C. L. Baker, E. B. Bonawitz, V. K Mansinghka, A. Gopnik, H. Wellman, L. Schulz, J. B. Tenenbaum:
      Proceedings of the Twenty-Eighth Annual Conference of the Cognitive Science Society
      #social cognition

      Learning cross-cutting systems of categories. (pdf) (bibtex)

      P. Shafto, C. Kemp, V. Mansignhka, M. Gordon, J. B. Tenenbaum:
      Proceedings of the Twenty-Eighth Annual Conference of the Cognitive Science Society

      Learning overhypotheses. (pdf) (bibtex)

      C. Kemp, A. Perfors, J. B. Tenenbaum:
      Proceedings of the Twenty-Eighth Annual Conference of the Cognitive Science Society

      Learning systems of concepts with an infinite relational model. (pdf) (bibtex)

      C. Kemp, J. B. Tenenbaum, T. L. Griffiths, T. Yamada, N. Ueda:
      Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI-06)

      Nonsense and sensibility: Inferring unseen possibilities. (pdf) (bibtex)

      L. A. Schmidt, C. Kemp, J. B. Tenenbaum:
      Proceedings of the Twenty-Eighth Annual Conference of the Cognitive Science Society

      Optimal predictions in everyday cognition (pdf) (bibtex)

      T. L. Griffiths, J. B. Tenenbaum:
      Psychological Science 17

      Poverty of the Stimulus? A rational approach. (pdf) (bibtex)

      A. Perfors, T. Regier, Tenenbaum, J. B.:
      Proceedings of the Twenty-Eighth Annual Conference of the Cognitive Science Society

      Probabilistic models of cognition: Conceptual foundations (pdf) (bibtex)

      N. Chater, J. B. Tenenbaum, A. Yuille:
      Trends in Cognitive Sciences, 10

      Statistics and the Bayesian mind (pdf) (bibtex)

      T. L. Griffiths, J. B. Tenenbaum:
      Significance 3

      Structured priors for structure learning. (pdf) (bibtex)

      V. K. Mansinghka, C. Kemp, J. B. Tenenbaum, T. L. Griffiths:
      Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI 2006)

      Theory-based Bayesian models of inductive learning and reasoning (pdf) (bibtex)

      J. B. Tenenbaum, T. L. Griffiths, C. Kemp:
      Trends in Cognitive Sciences, 10

      Unsupervised topic modelling for multi-party spoken discourse (pdf) (bibtex)

      M. Purver, K. P. Kording, T. L. Griffiths, J. B. Tenenbaum:
      Proceedings of Coling/ACL 2006.

2005

      A generative theory of similarity (pdf) (bibtex)

      C. Kemp, A. Bernstein, J. B. Tenenbaum:
      Proceedings of the Twenty-Seventh Annual Conference of the Cognitive Science Society.

      Context-sensitive induction (pdf) (bibtex)

      P. Shafto, C. Kemp, L. Baraff, J. Coley, J. B. Tenenbaum:
      Proceedings of the Twenty-Seventh Annual Conference of the Cognitive Science Society.

      Integrating topics and syntax (pdf) (bibtex)

      T. L. Griffiths, M. Steyvers, D. Blei, J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 17.

      Parametric Embedding for Class Visualization (pdf) (bibtex)

      T. Iwata, K. Saito, N. Ueda, S. Stromsten, T. L. Griffiths, J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 17

      Secret agents: inferences about hidden causes by 10- and 12-month-old infants (pdf) (bibtex)

      R. Saxe, J. B. Tenenbaum, S. Carey:
      Psychological Science 16
      #social cognition

      Structure and strength in causal induction (pdf) (bibtex)

      T. L. Griffiths, J. B. Tenenbaum:
      Cognitive Psychology 51

      The large-scale structure of semantic networks: statistical analyses and a model of semantic growth (pdf) (bibtex)

      M. Steyvers, J. B. Tenenbaum:
      Cognitive Science

      Word learning as Bayesian inference: Evidence from preschoolers (pdf) (bibtex)

      F. Xu, J. B. Tenenbaum:
      Proceedings of the Twenty-Seventh Annual Conference of the Cognitive Science Society.

2004

      Children’s causal inferences from indirect evidence: Backwards blocking and Bayesian reasoning in preschoolers (pdf) (bibtex)

      D. Sobel, J. B. Tenenbaum, A. Gopnik:
      Cognitive Science

      Discovering latent classes in relational data (pdf) (bibtex)

      C. Kemp, T. L. Griffiths, J. B. Tenenbaum:
      MIT AI Memo

      From algorithmic to subjective randomness (pdf) (bibtex)

      T. L. Griffiths, J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 16.

      Hierarchical topic models and the nested Chinese restaurant process (pdf) (bibtex)

      D. Blei, T. L. Griffiths, M. I. Jordan, J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 16.

      Learning domain structures (pdf) (bibtex)

      C. S. Kemp, A. Perfors, J. B. Tenenbaum:
      Proceedings of the Twenty-Sixth Annual Conference of the Cognitive Science Society.

      Semi-supervised learning with trees (pdf) (bibtex)

      C. Kemp, T. L Griffiths, S. Stromsten, J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 16.

      Using physical theories to infer hidden causal structure (pdf) (bibtex)

      T. L. Griffiths, E. R. Baraff, J. B. Tenenbaum:
      Proceedings of the Twenty-Sixth Annual Conference of the Cognitive Science Society.

2003

      Dynamical causal learning (pdf) (bibtex)

      D. Danks, T.L. Griffiths, J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 15

      Inferring causal networks from observations and interventions (pdf) (bibtex)

      M. Steyvers, J. B. Tenenbaum, E. J. Wagenmakers, B. Blum:
      Cognitive Science

      Learning causal laws (pdf) (bibtex)

      J. B. Tenenbaum, S. Niyogi:
      Proceedings of the Twenty-Fifth Annual Conference of the Cognitive Science Society.

      Learning style translation for the lines of a drawing (pdf) (bibtex)

      W.T. Freeman, J.B. Tenenbaum, E. Pasztor:
      ACM Transactions on Graphics

      Probability, algorithmic complexity, and subjective randomness (pdf) (bibtex)

      T. L. Griffiths, J. B. Tenenbaum:
      Proceedings of the Twenty-Fifth Annual Conference of the Cognitive Science Society.

      The role of causal models in reasoning under uncertainty (pdf) (bibtex)

      T. R. Krynski, J. B. Tenenbaum:
      Proceedings of the Twenty-Fifth Annual Conference of the Cognitive Science Society.

      Theory-based causal inference (pdf) (bibtex)

      J. B. Tenenbaum, T. L. Griffiths:
      Advances in Neural Information Processing Systems 15

      Theory-based induction (pdf) (bibtex)

      C. S. Kemp, J. B. Tenenbaum:
      Proceedings of the Twenty-Fifth Annual Conference of the Cognitive Science Society.

      V1 neurons signal acquisition of an internal representation of stimulus location (pdf) (bibtex)

      J. Sharma, V. Dragoi, J. B. Tenenbaum, E. K. Miller, M. Sur:
      Science

2002

      Bayesian models of inductive generalization (pdf) (bibtex)

      N. Sanjana, J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 15.

      Global versus local methods in nonlinear dimensionality reduction (pdf) (bibtex)

      V. de Silva, J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 15.

      The Isomap Algorithm and Topological Stability (pdf) (bibtex)

      M. Balasubramanian, E. L. Shwartz, J. B. Tenenbaum, V. de Silva, J. C. Langford:
      Science

      Unsupervised learning of curved manifolds (pdf) (bibtex)

      V. de Silva, J.B. Tenenbaum:
      Nonlinear Estimation and Classification ,

2001

      Randomness and coincidences: Reconciling intuition and probability theory (pdf) (bibtex)

      T. L. Griffiths, J. B. Tenenbaum:
      23rd Annual Conference of the Cognitive Science Society
      #coincidences

      Some specifics about generalization (bibtex)

      J. B. Tenenbaum, T. L. Griffiths:
      Behavioral and Brain Sciences
      #generalization

      Structure learning in human causal induction (pdf) (bibtex)

      J. B. Tenenbaum, T. L. Griffiths:
      Advances in Neural Information Processing Systems 13
      #causality, #structure

      The rational basis of representativeness (pdf) (bibtex)

      J. B. Tenenbaum, T. L. Griffiths:
      23rd Annual Conference of the Cognitive Science Society
      #categories

2000

      A global geometric framework for nonlinear dimensionality reduction (pdf) (bibtex)

      J. B. Tenenbaum, V. De Silva, J. C. Langford:
      Science
      #dimensionality reduction

      Rules and similarity in concept learning (pdf) (bibtex)

      J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 12
      #exemplars, #rules

      Separating style and content with bilinear models (pdf) (bibtex)

      J. B. Tenenbaum, W. T. Freeman:
      Neural Computation
      #singular value decomposition, #expectation-maximization

      Teacakes, trains, toxins, and taxicabs: A Bayesian account of predicting the future (pdf) (bibtex)

      T. L. Griffiths, J. B. Tenenbaum:
      Proceedings of the 22nd Annual Conference of the Cognitive Science Society
      #prediction

      Word learning as Bayesian inference (pdf) (bibtex)

      J. B. Tenenbaum, F. Xu:
      Proceedings of the 22nd Annual Conference of the Cognitive Science Society
      #language

1999

      A Bayesian Framework for Concept Learning (pdf) (bibtex)

      J. B. Tenenbaum:
      Ph.D. Thesis, MIT
      #concept learning

      Bayesian modeling of human concept learning (pdf) (bibtex)

      J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 11
      #concept learning

1998

      Mapping a manifold of perceptual observations (pdf) (bibtex)

      J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 10
      #dimensionality reduction

1995

      Learning the structure of similarity (pdf) (bibtex)

      J. B. Tenenbaum:
      Advances in Neural Information Processing Systems 8
      #structure, #generalization

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