Publications – Computational Cognitive Science

2023

Evaluating statistical language models as pragmatic reasoners (pdf) (bibtex)

Benjamin Lipkin, Lionel Wong, Gabriel Grand, Joshua B Tenenbaum

Proceedings of the Annual Meeting of the Cognitive Science Society

#language, #pragmatics, #inference

2022

Designing Perceptual Puzzles by Differentiating Probabilistic Programs (pdf) (bibtex)

Kartik Chandra, Tzu-Mao Li, Joshua Tenenbaum, Jonathan Ragan-Kelley

SIGGRAPH

#perception, #illusions, #automatic differentiation, #probabilistic programming

Map Induction: Compositional spatial submap learning for efficient exploration in novel environments (web) (bibtex)

Sugandha Sharma, Aidan Curtis, Marta Kryven, Josh Tenenbaum, Ila Fiete

10th International Conference on Learning Representations (ICLR)

#hierarchical bayesian framework, #program induction, #spatial navigation, #planning, #exploration, #map/structure learning

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

Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration (pdf) (bibtex)

Xavier Puig, Tianmin Shu, Shuang Li, Zilin Wang, Joshua B. Tenenbaum, Sanja Fidler, Antonio Torralba

9th International Conference on Learning Representations (ICLR)

#human-ai collaboration, #social perception, #multi-agent system, #embodied ai

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

The Child as Hacker (pdf) (doi) (bibtex)

Joshua S. Rule, Joshua B. Tenenbaum, Steven T. Piantadosi

Trends in Cognitive Science

#computational modeling, #hacking, #language of thought, #learning and cognitive development, #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

ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics (web) (bibtex)

Yuanming Hu, Jiancheng Liu, Andrew Spielberg, Joshua B. Tenenbaum, William T. Freeman, Jiajun Wu, Daniela Rus, Wojciech Matusik

IEEE International Conference on Robotics and Automation (ICRA)

#dynamics modeling, #deep learning, #robotics

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

Learning to Describe Scenes with Programs (web) (bibtex)

Yunchao Liu, Zheng Wu, Daniel Ritchie, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu

International Conference on Learning Representations (ICLR)

#neuro-symbolic algorithms, #computer vision, #scene understanding

Learning to Infer and Execute 3D Shape Programs (web) (bibtex)

Yonglong Tian, Andrew Luo, Xingyuan Sun, Kevin Ellis, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu

International Conference on Learning Representations (ICLR)

#neuro-symbolic algorithms, #shape modeling, #computer vision

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

Program-Guided Image Manipulators (bibtex)

Jiayuan Mao, Xiuming Zhang, Yikai Li, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu

IEEE International Conference on Computer Vision (ICCV)

#neuro-symbolic algorithms, #deep learning, #computer vision

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

3D-Aware Scene Manipulation via Inverse Graphics (web) (bibtex)

Shunyu Yao, Tzu-Ming Harry Hsu, Jun-Yan Zhu, Jiajun Wu, Antonio Torralba, William T. Freeman, Joshua B. Tenenbaum

Advances in Neural Information Processing Systems (NeurIPS)

#3d vision, #deep learning, #scene understanding

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 Exploit Stability for 3D Scene Parsing (web) (bibtex)

Yilun Du, Zhijian Liu, Hector Basevi, Ales Leonardis, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu

Advances in Neural Information Processing Systems (NeurIPS)

#3d vision, #deep learning, #scene understanding

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

Physical Primitive Decomposition (web) (bibtex)

Zhijian Liu, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu

European Conference on Computer Vision (ECCV)

#3d vision, #deep learning, #intuitive physics

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

Seeing Tree Structure from Vibration (web) (bibtex)

Tianfan Xue, Jiajun Wu, Zhoutong Zhang, Chengkai Zhang, Joshua B. Tenenbaum, William T. Freeman

European Conference on Computer Vision (ECCV)

#computer vision, #hierarchical bayes, #scene understanding

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

Eye-Tracking Causality (web) (doi) (bibtex)

Tobias Gerstenberg, Matthew F Peterson, Noah D Goodman, David A Lagnado, Joshua B Tenenbaum

Psychological Science

#causality, #counterfactuals, #mental simulation, #intuitive physics, #eye tracking, #open data, #open materials

A Compositional Object-Based Approach To Learning Physical Dynamics (web) (bibtex)

Michael Chang, Tomer Ullman, Antonio Torralba, Joshua B. Tenenbaum

Proceedings of the 5th International Conference on Learning Representations

#intuitive physics, #simulation, #deep learning, #unsupervised learning, #scene understanding

Building Machines That Learn and Think Like People (web) (doi) (bibtex)

Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, Samuel J Gershman

Behavioral and Brain Sciences

#artificial intelligence, #intuitive theories, #intuitive physics, #intuitive psychology, #compositionality, #learning to learn

Causal learning from interventions and dynamics in continuous time (pdf) (bibtex)

Neil R. Bramley, Ralf Mayrhofer, Tobias Gerstenberg, David A. Lagnado

Proceedings of the 39th Annual Conference of the Cognitive Science Society

#causal learning, #intervention, #time, #causal cycles, #structure induction, #dynamics

Causation in legal and moral reasoning (pdf) (bibtex)

David A. Lagnado, Tobias Gerstenberg

Oxford Handbook of Causal Reasoning

#causal reasoning, #moral reasoning, #counterfactuals

Faulty towers: A hypothetical simulation model of physical support (pdf) (bibtex)

Tobias Gerstenberg, Liang Zhou, Kevin A. Smith, Joshua B. Tenenbaum

Proceedings of the 39th Annual Conference of the Cognitive Science Society

#causality, #counterfactual, #hypothetical, #mental simulation, #intuitive physics, #physical support

Generative Modeling of Audible Shapes for Object Perception (pdf) (bibtex)

Zhoutong Zhang, Jiajun Wu, Qiujia Li, Zhengjia Huang, James Traer, Josh H. McDermott, Joshua B. Tenenbaum, William T. Freeman

IEEE International Conference on Computer Vision (ICCV)

#deep learning, #simulation, #auditory perception, #scene understanding

Intuitive Theories (pdf) (bibtex)

Tobias Gerstenberg, Joshua B. Tenenbaum

Oxford Handbook of Causal Reasoning

#intuitive theories, #causality, #counterfactuals, #intuitive physics, #intuitive psychology

Learning to See Physics via Visual De-animation (web) (bibtex)

Jiajun Wu, Erika Lu, Pushmeet Kohli, William T. Freeman, Joshua B. Tenenbaum

Advances in Neural Information Processing Systems (NIPS)

#intuitive physics, #simulation, #deep learning, #scene understanding

Marbles in Inaction: Counterfactual Simulation and Causation by Omission (pdf) (bibtex)

Simon Stephan, Pascale Willemsen, Tobias Gerstenberg

Proceedings of the 39th Annual Conference of the Cognitive Science Society

#causality, #counterfactuals, #causation by omission, #causal attribution, #mental simulation, #intuitive physics

MarrNet: 3D Shape Reconstruction via 2.5D Sketches (web) (bibtex)

Jiajun Wu, Yifan Wang, Tianfan Xue, Xingyuan Sun, William T. Freeman, Joshua B. Tenenbaum

Advances in Neural Information Processing Systems (NIPS)

#3d vision, #deep learning

Neural Scene De-rendering (web) (bibtex)

Jiajun Wu, Joshua B. Tenenbaum, Pushmeet Kohli

IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

#deep learning, #self-supervised learning, #inverse graphics, #computer vision, #scene understanding

Physical problem solving: Joint planning with symbolic, geometric, and dynamic constraints (pdf) (bibtex)

Ilker Yildirim, Tobias Gerstenberg, Basil Saeed, Marc Toussant, Joshua B. Tenenbaum

Proceedings of the 39th Annual Conference of the Cognitive Science Society

#planning, #problem solving, #logic-geometric programming, #intuitive physics, #scene understanding

Self-Supervised Intrinsic Image Decomposition (web) (bibtex)

Michael Janner, Jiajun Wu, Tejas D. Kulkarni, Ilker Yildirim, Joshua B. Tenenbaum

Advances in Neural Information Processing Systems (NIPS)

#computer vision, #deep learning, #self-supervised learning

Shape and Material from Sound (web) (bibtex)

Zhoutong Zhang, Qiujia Li, Zhengjia Huang, Jiajun Wu, Joshua B. Tenenbaum, William T. Freeman

Advances in Neural Information Processing Systems (NIPS)

#auditory perception, #deep learning, #simulation

Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes with Deep Generative (web) (doi) (bibtex)

Amir Arsalan Soltani, Haibin Huang, Jiajun Wu, Tejas D Kulkarni, Joshua B Tenenbaum

IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

#2d to 3d, #3d vision, #3d generation, #3d reconstruction, #inverse vision, #scene understanding, #deep learning

Ten-month-old infants infer the value of goals from the costs of actions (web) (doi) (bibtex)

Shari Liu, Tomer D Ullman, Joshua B Tenenbaum, Elizabeth S Spelke

Science

#intuitive psychology, #inverse planning, #action-value prediction

Thinking inside the box: Motion prediction in contained spaces uses simulation (pdf) (bibtex)

Kevin A Smith, Filipe de A B Peres, Edward Vul, Joshua B Tenenbaum

Cognitive Science Society

#intuitive physics, #simulation, #topology, #containers

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

Physics 101: Learning Physical Object Properties from Unlabeled Videos (web) (bibtex)

Jiajun Wu, Joseph J. Lim, Hongyi Zhang, Joshua B. Tenenbaum, William T. Freeman

British Machine Vision Conference (BMVC)

#intuitive physics, #unsupervised learning, #deep learning, #scene understanding

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

Sam Gershman*, Tobias Gerstenberg*, Chris Baker, Fiery Cushman

PLoS ONE

#planning, #theory of mind, #habit

Single Image 3D Interpreter Network (web) (bibtex)

Jiajun Wu, Tianfan Xue, Joseph J. Lim, Yuandong Tian, Joshua B. Tenenbaum, Antonio Torralba, William T. Freeman

European Conference in Computer Vision (ECCV)

#deep learning, #self-supervised learning, #3d vision

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

Causal superseding (pdf) (bibtex)

Jonathan Kominsky, Jonathan Phillips, Tobias Gerstenberg, David Lagnado, Joshua Knobe

Cognition

#causality, #attribution, #counterfactuals, #normality

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

Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning (web) (bibtex)

Jiajun Wu, Ilker Yildirim, Joseph J. Lim, William T. Freeman, Joshua B. Tenenbaum

Advances in Neural Information Processing Systems (NIPS)

#intuitive physics, #simulation, #deep learning, #unsupervised learning, #scene understanding

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

Human-Level Concept Learning Through Probabilistic Program Induction (web) (doi) (bibtex)

Brenden M Lake, Ruslan Salakhutdinov, Joshua B Tenenbaum

Science

#concept learning, #program induction, #motor skills, #artificial intelligence, #learning to learn, #bayesian, #one-shot learning

Inference of intention and permissibility in moral decision making (pdf) (bibtex)

Max Kleiman-Weiner, Tobias Gerstenberg, Sydney Levine, Joshua B. Tenebaum

Proceedings of the 37th Annual Conference of the Cognitive Science Society

#moral judgment, #social cognition, #intention, #theory of mind, #influence diagrams, #counterfactuals

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

Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs (pdf) (bibtex)

Vikash Mansinghka*, Tejas Kulkarni*, Yura Perov, Josh Tenenbaum

NIPS 2013

#probabilistic programming, #computational vision, #inverse graphics, #mcmc

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

Causal responsibility and counterfactuals (pdf) (bibtex)

D.A. Lagnado, T. Gerstenberg, R. Zultan

Cognitive Science

#causality, #counterfactuals, #responsibility attribution, #shared responsibility, #pivotality, #criticality

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

Observing and intervening: Rational and heuristic models of causal decision making (pdf) (bibtex)

B. Meder, T. Gerstenberg, Y. Hagmayer, M. Waldmann

The Open Psychology Journal

#causal reasoning, #causal decision making, #bayesian networks, #rational inference, #bounded rationality, #heuristics, # computer simulation

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

Action understanding as inverse planning (pdf) (bibtex)

C. L. Baker, R. Saxe, J. B. Tenenbaum

Cognition

#action understanding, #goal inference, #theory of mind, #inverse 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

The Infinite Latent Events Model (pdf) (bibtex)

D. Wingate, N. D. Goodman, D. M. Roy and J. B. Tenenbaum

Uncertainty in Artificial Intelligence

#bayesian nonparametrics, #infinite, #dynamical system

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

Generalization, similarity, and Bayesian inference (pdf) (bibtex)

J. B. Tenenbaum, T. L. Griffiths

Behavioral and Brain Sciences

#additive clustering, #categorization, #concept learning, #contrast model, #features, #generalization, #psychological space, #similarity

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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