Joshua Tenenbaum

Q: What Schools Are Affiliated With Joshua Tenenbaum

Joshua Tenenbaum is affiliated with the following schools: Yale University, Stanford University, Massachusetts Institute of Technology, Johns Hopkins University

Joshua Tenenbaum's AcademicInfluence.com Rankings

Joshua Tenenbaum

Psychology

#209

World Rank

#311

Historical Rank

#144

USA Rank

Cognitive Science

#27

World Rank

#27

Historical Rank

#13

USA Rank

psychology Degrees

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Psychology

Joshua Tenenbaum's Degrees

Bachelors Cognitive Science Stanford University

Why Is Joshua Tenenbaum Influential?

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According to Wikipedia, Joshua Brett Tenenbaum is Professor of Computational Cognitive Science at the Massachusetts Institute of Technology. He is known for contributions to mathematical psychology and Bayesian cognitive science. According to the MacArthur Foundation, which named him a MacArthur Fellow in 2019, "Tenenbaum is one of the first to develop and apply probabilistic and statistical modeling to the study of human learning, reasoning, and perception, and to show how these models can explain a fundamental challenge of cognition: how our minds understand so much from so little, so quickly."

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Joshua Tenenbaum's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

A global geometric framework for nonlinear dimensionality reduction. (2000) (13289)
Human-level concept learning through probabilistic program induction (2015) (2445)
Building machines that learn and think like people (2016) (1858)
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling (2016) (1551)
How to Grow a Mind: Statistics, Structure, and Abstraction (2011) (1446)
The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth (2001) (1243)
Hierarchical Topic Models and the Nested Chinese Restaurant Process (2003) (1120)
Topics in semantic representation. (2007) (1072)
Global Versus Local Methods in Nonlinear Dimensionality Reduction (2002) (935)
Meta-Learning for Semi-Supervised Few-Shot Classification (2018) (917)
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation (2016) (906)
Deep Convolutional Inverse Graphics Network (2015) (904)
Separating Style and Content with Bilinear Models (2000) (901)
Word learning as Bayesian inference. (2007) (900)
Causal Inference in Multisensory Perception (2007) (831)
Theory-based Bayesian models of inductive learning and reasoning (2006) (772)
Church: a language for generative models (2008) (770)
Learning Systems of Concepts with an Infinite Relational Model (2006) (747)
Action understanding as inverse planning (2009) (742)
One shot learning of simple visual concepts (2011) (712)
Generalization, similarity, and Bayesian inference. (2001) (708)
Integrating Topics and Syntax (2004) (615)
Simulation as an engine of physical scene understanding (2013) (608)
Structure and strength in causal induction (2005) (595)
The discovery of structural form (2008) (569)
Bayesian models of cognition (2008) (548)
Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need? (2020) (512)
Optimal Predictions in Everyday Cognition (2006) (508)
Probabilistic models of cognition: Conceptual foundations (2006) (498)
Machine behaviour (2019) (495)
Probabilistic models of cognition: exploring representations and inductive biases (2010) (475)
Inferring causal networks from observations and interventions (2003) (473)
Computational rationality: A converging paradigm for intelligence in brains, minds, and machines (2015) (452)
The Neuro-Symbolic Concept Learner: Interpreting Scenes Words and Sentences from Natural Supervision (2019) (449)
Structure Discovery in Nonparametric Regression through Compositional Kernel Search (2013) (444)
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding (2018) (412)
The dynamics of memory as a consequence of optimal adaptation to a changing body (2007) (407)
Learning overhypotheses with hierarchical Bayesian models. (2007) (393)
A Compositional Object-Based Approach to Learning Physical Dynamics (2016) (370)
One and Done? Optimal Decisions From Very Few Samples (2014) (347)
A Rational Analysis of Rule-Based Concept Learning (2008) (339)
Learning to share visual appearance for multiclass object detection (2011) (339)
Theory-based causal induction. (2009) (335)
Using Speakers' Referential Intentions to Model Early Cross-Situational Word Learning (2009) (326)
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks (2018) (324)
Children's causal inferences from indirect evidence: Backwards blocking and Bayesian reasoning in preschoolers (2004) (321)
Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning (2015) (318)
Mapping a Manifold of Perceptual Observations (1997) (317)
ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models (2019) (317)
Graph approximations to geodesics on embedded manifolds (2000) (301)
Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling (2018) (300)
End-to-End Differentiable Physics for Learning and Control (2018) (293)
A critical period for second language acquisition: Evidence from 2/3 million English speakers (2018) (283)
Single Image 3D Interpreter Network (2016) (278)
Sparse multidimensional scaling using land-mark points (2004) (277)
Modelling Relational Data using Bayesian Clustered Tensor Factorization (2009) (271)
Rational quantitative attribution of beliefs, desires and percepts in human mentalizing (2017) (268)
CLEVRER: CoLlision Events for Video REpresentation and Reasoning (2019) (248)
Structured statistical models of inductive reasoning. (2009) (245)
Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning (2018) (241)
Pure Reasoning in 12-Month-Old Infants as Probabilistic Inference (2011) (233)
Bayesian Theory of Mind: Modeling Joint Belief-Desire Attribution (2011) (229)
A tutorial introduction to Bayesian models of cognitive development (2011) (228)
The learnability of abstract syntactic principles (2011) (227)
MarrNet: 3D Shape Reconstruction via 2.5D Sketches (2017) (223)
Learning with Hierarchical-Deep Models (2013) (219)
One-shot learning by inverting a compositional causal process (2013) (218)
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) (218)
Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids (2018) (216)
Automatic Construction and Natural-Language Description of Nonparametric Regression Models (2014) (213)
The Naïve Utility Calculus: Computational Principles Underlying Commonsense Psychology (2016) (201)
Sensitivity to sampling in Bayesian word learning. (2007) (200)
Visual Object Networks: Image Generation with Disentangled 3D Representations (2018) (198)
Bayesian Modeling of Human Concept Learning (1998) (196)
Infants consider both the sample and the sampling process in inductive generalization (2010) (193)
Learning a theory of causality. (2011) (192)
The role of causality in judgment under uncertainty. (2007) (192)
Flexible Neural Representation for Physics Prediction (2018) (191)
Picture: A probabilistic programming language for scene perception (2015) (190)
Learning to Infer Graphics Programs from Hand-Drawn Images (2017) (189)
A probabilistic model of visual working memory: Incorporating higher order regularities into working memory capacity estimates. (2013) (188)
Synthesizing 3D Shapes via Modeling Multi-view Depth Maps and Silhouettes with Deep Generative Networks (2017) (182)
The mentalistic basis of core social cognition: experiments in preverbal infants and a computational model. (2013) (180)
Infinite Mixture Prototypes for Few-Shot Learning (2019) (176)
The Isomap Algorithm and Topological Stability (2002) (176)
Unsupervised Topic Modelling for Multi-Party Spoken Discourse (2006) (175)
One-Shot Learning with a Hierarchical Nonparametric Bayesian Model (2011) (166)
Learning to See Physics via Visual De-animation (2017) (164)
Separating Style and Content (1996) (163)
ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics (2018) (161)
Bootstrapping in a language of thought: A formal model of numerical concept learning (2012) (158)
Help or Hinder: Bayesian Models of Social Goal Inference (2009) (158)
Modeling human performance in statistical word segmentation (2010) (158)
Structure Learning in Human Causal Induction (2000) (153)
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation (2020) (150)
Secret Agents (2005) (144)
Goal Inference as Inverse Planning (2007) (142)
Discovering Structure by Learning Sparse Graphs (2010) (142)
Entity Abstraction in Visual Model-Based Reinforcement Learning (2019) (142)
The neural architecture of language: Integrative modeling converges on predictive processing (2020) (138)
Variability, negative evidence, and the acquisition of verb argument constructions. (2010) (137)
Music Gesture for Visual Sound Separation (2020) (137)
Learning Shape Priors for Single-View 3D Completion and Reconstruction (2018) (135)
Learning bilinear models for two-factor problems in vision (1997) (134)
Mind Games: Game Engines as an Architecture for Intuitive Physics (2017) (129)
A Bayesian framework for concept learning (1999) (129)
Bayesian models of human action understanding (2005) (123)
Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model (2009) (121)
Multistability and Perceptual Inference (2012) (121)
From mere coincidences to meaningful discoveries (2007) (120)
Neural Scene De-rendering (2017) (119)
Bayesian networks, Bayesian learning and cognitive development. (2007) (118)
Physics 101: Learning Physical Object Properties from Unlabeled Videos (2016) (116)
Write, Execute, Assess: Program Synthesis with a REPL (2019) (112)
Intuitive Theories of Mind: A Rational Approach to False Belief (2005) (112)
Learning to Reconstruct Shapes from Unseen Classes (2018) (112)
The logical primitives of thought: Empirical foundations for compositional cognitive models. (2016) (110)
Learning to Infer and Execute 3D Shape Programs (2019) (110)
Discovering Latent Classes in Relational Data (2004) (110)
Ten-month-old infants infer the value of goals from the costs of actions (2017) (109)
Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering (2021) (108)
Poverty of the Stimulus? A Rational Approach (2006) (105)
Residual Policy Learning (2018) (105)
Reduction A Global Geometric Framework for Nonlinear Dimensionality (2011) (105)
Concepts in a Probabilistic Language of Thought (2014) (104)
Self-Supervised Intrinsic Image Decomposition (2017) (104)
Functional neuroanatomy of intuitive physical inference (2016) (103)
Going beyond the evidence: Abstract laws and preschoolers’ responses to anomalous data (2008) (103)
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs (2013) (103)
Neural Radiance Flow for 4D View Synthesis and Video Processing (2020) (103)
Reasoning About Physical Interactions with Object-Oriented Prediction and Planning (2018) (102)
Exploiting compositionality to explore a large space of model structures (2012) (100)
Intuitive theories as grammars for causal inference (2007) (98)
Theory-Based Causal Inference (2002) (96)
A Bayesian Framework for Cross-Situational Word-Learning (2007) (95)
DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning (2020) (93)
Look, Listen, and Act: Towards Audio-Visual Embodied Navigation (2019) (92)
Propagation Networks for Model-Based Control Under Partial Observation (2018) (92)
Bias reformulation for one-shot function induction (2014) (91)
Parametric Embedding for Class Visualization (2004) (91)
Coordinate to cooperate or compete: Abstract goals and joint intentions in social interaction (2016) (90)
Social and Discourse Contributions to the Determination of Reference in Cross-Situational Word Learning (2013) (90)
A probabilistic model of theory formation (2010) (89)
Modeling Human Plan Recognition Using Bayesian Theory of Mind (2014) (89)
Bayes and Blickets: Effects of Knowledge on Causal Induction in Children and Adults (2011) (89)
Children’s understanding of the costs and rewards underlying rational action (2015) (88)
The Rational Basis of Representativeness (2001) (88)
Learning with AMIGo: Adversarially Motivated Intrinsic Goals (2020) (87)
Learning to Learn Causal Models (2010) (87)
Rules and Similarity in Concept Learning (1999) (86)
The Omniglot challenge: a 3-year progress report (2019) (85)
Human Learning in Atari (2017) (85)
Learning to Infer Program Sketches (2019) (84)
Theory learning as stochastic search in the language of thought (2012) (84)
Toward the neural implementation of structure learning (2016) (82)
Structured Priors for Structure Learning (2006) (81)
Relational inductive bias for physical construction in humans and machines (2018) (81)
See, feel, act: Hierarchical learning for complex manipulation skills with multisensory fusion (2019) (80)
Dynamic Infinite Relational Model for Time-varying Relational Data Analysis (2010) (80)
Compositional inductive biases in function learning (2016) (79)
Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing (2018) (79)
Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense (2020) (76)
DensePhysNet: Learning Dense Physical Object Representations via Multi-step Dynamic Interactions (2019) (74)
Semi-Supervised Learning with Trees (2003) (73)
3D-Aware Scene Manipulation via Inverse Graphics (2018) (73)
Indirect Evidence and the Poverty of the Stimulus: The Case of Anaphoric One (2009) (73)
Unsupervised Learning by Program Synthesis (2015) (73)
Learning style translation for the lines of a drawing (2003) (73)
Inferring mass in complex scenes by mental simulation (2016) (71)
Foley Music: Learning to Generate Music from Videos (2020) (71)
3D Shape Perception from Monocular Vision, Touch, and Shape Priors (2018) (70)
Learning Compositional Rules via Neural Program Synthesis (2020) (69)
Dynamical Causal Learning (2002) (69)
Noisy Newtons: Unifying process and dependency accounts of causal attribution (2012) (69)
Learning the Structure of Similarity (1995) (68)
How, whether, why: Causal judgments as counterfactual contrasts (2015) (67)
Efficient inverse graphics in biological face processing (2018) (66)
Stochastic Prediction of Multi-Agent Interactions from Partial Observations (2019) (66)
Improved Contrastive Divergence Training of Energy Based Models (2020) (66)
Learning annotated hierarchies from relational data (2006) (66)
DreamCoder: bootstrapping inductive program synthesis with wake-sleep library learning (2021) (65)
The Structure and Dynamics of Scientific Theories: A Hierarchical Bayesian Perspective* (2010) (64)
Eye-Tracking Causality (2017) (63)
Intuitive Theories (2020) (63)
Two proposals for causal grammars (2007) (63)
Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation (2021) (63)
Inductive Reasoning: Theory-Based Bayesian Models of Inductive Reasoning (2007) (62)
Humans predict liquid dynamics using probabilistic simulation (2015) (60)
Productivity and Reuse in Language (2011) (59)
The Variational Homoencoder: Learning to learn high capacity generative models from few examples (2018) (59)
Compositional Visual Generation with Composable Diffusion Models (2022) (59)
A probabilistic model of cross-categorization (2011) (58)
Learning Physical Graph Representations from Visual Scenes (2020) (58)
Planning with Diffusion for Flexible Behavior Synthesis (2022) (57)
PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics (2021) (57)
V1 Neurons Signal Acquisition of an Internal Representation of Stimulus Location (2003) (57)
Understanding Visual Concepts with Continuation Learning (2016) (57)
Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning (2021) (56)
Learning Causal Laws (2003) (56)
Cause and Intent: Social Reasoning in Causal Learning (2009) (56)
The three pillars of machine programming (2018) (55)
Inductive reasoning about causally transmitted properties (2008) (54)
Unsupervised Discovery of Parts, Structure, and Dynamics (2019) (54)
Predicting the future as Bayesian inference: people combine prior knowledge with observations when estimating duration and extent. (2011) (53)
Learning a commonsense moral theory (2017) (53)
The Large-Scale Structure of Semantic Networks (2005) (53)
Learning Libraries of Subroutines for Neurally-Guided Bayesian Program Induction (2018) (52)
Bootstrap Learning via Modular Concept Discovery (2013) (52)
Visualizing and Understanding Generative Adversarial Networks (Extended Abstract) (2019) (52)
Theory of Minds: Understanding Behavior in Groups Through Inverse Planning (2019) (51)
Three ideal observer models for rule learning in simple languages (2011) (50)
Unsupervised Learning of Curved Manifolds (2003) (49)
Inference of Intention and Permissibility in Moral Decision Making (2015) (49)
Unsupervised Learning of Latent Physical Properties Using Perception-Prediction Networks (2018) (49)
Randomness and Coincidences: Reconciling Intuition and Probability Theory (2001) (48)
Learning to Describe Scenes with Programs (2018) (48)
How Tall Is Tall? Compositionality, Statistics, and Gradable Adjectives (2009) (48)
A Comparative Evaluation of Approximate Probabilistic Simulation and Deep Neural Networks as Accounts of Human Physical Scene Understanding (2016) (47)
Not So Innocent (2015) (47)
One-shot learning of generative speech concepts (2014) (46)
Rapid trial-and-error learning with simulation supports flexible tool use and physical reasoning (2019) (46)
Intuitive experimentation in the physical world (2018) (45)
Learning to Share and Hide Intentions using Information Regularization (2018) (45)
Learning Causal Schemata (2007) (44)
An example-based approach to style translation for line drawings (1999) (44)
Theory-based Social Goal Inference (2008) (44)
Natively probabilistic computation (2009) (44)
A counterfactual simulation model of causal judgments for physical events. (2021) (43)
Modeling Semantic Cognition as Logical Dimensionality Reduction (2008) (43)
Learning Domain Structures (2004) (43)
Probabilistic models of cognition: where next? (2006) (43)
Fragment Grammars: Exploring Computation and Reuse in Language (2009) (43)
An integrated account of generalization across objects and features (2012) (42)
Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration (2020) (42)
Artificial Neural Networks Accurately Predict Language Processing in the Brain (2020) (42)
Nonparametric Bayesian Policy Priors for Reinforcement Learning (2010) (42)
Drivers are blamed more than their automated cars when both make mistakes (2019) (41)
From counterfactual simulation to causal judgment (2014) (41)
Visual Grounding of Learned Physical Models (2020) (41)
Online Developmental Science to Foster Innovation, Access, and Impact (2020) (41)
A Bayesian Model of the Acquisition of Compositional Semantics (2008) (41)
Learning and using relational theories (2007) (40)
Probability, algorithmic complexity, and subjective randomness (2003) (40)
The Naïve Utility Calculus as a unified, quantitative framework for action understanding (2020) (39)
Surprise! Infants consider possible bases of generalization for a single input example. (2014) (39)
Beating the World's Best at Super Smash Bros. with Deep Reinforcement Learning (2017) (38)
A Computational Model of Commonsense Moral Decision Making (2018) (38)
Informative communication in word production and word learning (2009) (38)
Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations (2019) (38)
Bayesian Policy Search with Policy Priors (2011) (37)
Learning Cross-cutting Systems of Categories (2006) (37)
Discovering hierarchical motion structure (2016) (37)
A theory of learning to infer (2019) (37)
Physical predictions over time (2013) (37)
Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoning (2021) (37)
A Generative Theory of Similarity (2005) (36)
A Morphable Face Albedo Model (2020) (36)
Using Physical Theories to Infer Hidden Causal Structure (2004) (36)
Online Bayesian Goal Inference for Boundedly-Rational Planning Agents (2020) (36)
Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks (2020) (35)
Learning to Learn with Compound HD Models (2011) (35)
The imaginary fundamentalists: The unshocking truth about Bayesian cognitive science (2011) (35)
The causes and consequences explicit in verbs (2015) (35)
Learning physical parameters from dynamic scenes (2018) (34)
Learning to learn categories (2009) (34)
Causal inference in sensorimotor integration (2006) (34)
Too Many Cooks: Coordinating Multi-agent Collaboration Through Inverse Planning (2020) (34)
Combining Physical Simulators and Object-Based Networks for Control (2019) (34)
Learning and Long-Term Retention of Large-Scale Artificial Languages (2013) (33)
Too Many Cooks: Bayesian Inference for Coordinating Multi-Agent Collaboration (2020) (33)
Generative Modeling of Audible Shapes for Object Perception (2017) (33)
Infinite Dynamic Bayesian Networks (2011) (33)
CrossCat: A Fully Bayesian Nonparametric Method for Analyzing Heterogeneous, High Dimensional Data (2015) (33)
Visual Concept-Metaconcept Learning (2020) (33)
Finding Friend and Foe in Multi-Agent Games (2019) (32)
Phrase similarity in humans and machines (2015) (31)
Theory Acquisition as Stochastic Search (2010) (31)
Bayesian Models of Inductive Generalization (2002) (31)
A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects (2020) (31)
Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language (2021) (31)
Bayesian Models of Conceptual Development: Learning as Building Models of the World (2020) (31)
Vector-based pedestrian navigation in cities (2021) (31)
The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark Towards Physically Realistic Embodied AI (2021) (30)
Theory-Based Induction (2003) (30)
Inferring the intentional states of autonomous virtual agents (2014) (30)
Logical Rule Induction and Theory Learning Using Neural Theorem Proving (2018) (30)
Learning physics from dynamical scenes (2014) (30)
Unsupervised Learning of Compositional Energy Concepts (2021) (30)
Modeling human intuitions about liquid flow with particle-based simulation (2018) (30)
End-to-End Optimization of Scene Layout (2020) (30)
Stochastic Digital Circuits for Probabilistic Inference (2008) (29)
How recursive is language? A Bayesian exploration (2010) (29)
Perceptual Multistability as Markov Chain Monte Carlo Inference (2009) (29)
Learning Symbolic Operators for Task and Motion Planning (2021) (28)
Modeling the acquisition of quantifier semantics : a case study in function word learnability (2012) (28)
Learning to Exploit Stability for 3D Scene Parsing (2018) (28)
Lucky or clever? From expectations to responsibility judgments (2018) (28)
Learning Structured Generative Concepts (2010) (27)
Elements of a stochastic 3D prediction engine in larval zebrafish prey capture (2019) (27)
From Algorithmic to Subjective Randomness (2003) (27)
Inferring human intent from video by sampling hierarchical plans (2016) (27)
Theory Acquisition and the Language of Thought (2008) (27)
Assessing the Perceived Predictability of Functions (2015) (26)
Rational Inference of Beliefs and Desires From Emotional Expressions (2017) (26)
The neural architecture of language: Integrative reverse-engineering converges on a model for predictive processing (2020) (26)
The Child as Hacker (2020) (26)
Human collective intelligence as distributed Bayesian inference (2016) (26)
Dissociating language and thought in large language models: a cognitive perspective (2023) (25)
The Tools Challenge: Rapid Trial-and-Error Learning in Physical Problem Solving (2019) (25)
Probing the Compositionality of Intuitive Functions (2016) (25)
Physion: Evaluating Physical Prediction from Vision in Humans and Machines (2021) (25)
Towards common-sense reasoning via conditional simulation: legacies of Turing in Artificial Intelligence (2012) (25)
Spatial Attention and Temporal Expectation Under Timed Uncertainty Predictably Modulate Neuronal Responses in Monkey V1. (2015) (25)
Unsupervised Discovery of 3D Physical Objects from Video (2020) (25)
Learning to Compose Visual Relations (2021) (24)
Learning Grounded Causal Models (2007) (24)
Learning What is Where from Social Observations (2012) (24)
Leveraging Language to Learn Program Abstractions and Search Heuristics (2021) (24)
Reasoning About Physical Interactions with Object-Centric Models (2018) (24)
Graph theoretic analyses of semantic networks: Small worlds in semantic networks (2005) (24)
3D Interpreter Networks for Viewer-Centered Wireframe Modeling (2018) (24)
Learning Overhypotheses (2006) (24)
Sampling for Bayesian Program Learning (2016) (23)
Efficient analysis-by-synthesis in vision: A computational framework, behavioral tests, and modeling neuronal representations (2015) (23)
Children Understand That Agents Maximize Expected Utilities (2017) (23)
Invariant representations of mass in the human brain (2019) (23)
Probabilistic models of cognition. Special Issue. (2006) (23)
PTR: A Benchmark for Part-based Conceptual, Relational, and Physical Reasoning (2021) (23)
Concept learning as motor program induction: A large-scale empirical study (2012) (23)
Inverse Graphics with Probabilistic CAD Models (2014) (22)
Physical Primitive Decomposition (2018) (22)
Relevant and Robust (2015) (22)
Shape and Material from Sound (2017) (22)
A stochastic programming perspective on nonparametric Bayes (2008) (22)
Few-Shot Bayesian Imitation Learning with Logical Program Policies (2019) (21)
Online learning of symbolic concepts (2017) (21)
Learning Signal-Agnostic Manifolds of Neural Fields (2021) (21)
AGENT: A Benchmark for Core Psychological Reasoning (2021) (21)
Deep Audio Priors Emerge From Harmonic Convolutional Networks (2020) (21)
A Probabilistic Model of Meetings That Combines Words and Discourse Features (2008) (21)
Prompting Decision Transformer for Few-Shot Policy Generalization (2022) (20)
Constructing Social Preferences From Anticipated Judgments: When Impartial Inequity is Fair and Why? (2017) (20)
World model learning and inference (2021) (20)
Library learning for neurally-guided Bayesian program induction (2018) (20)
An integrative computational architecture for object-driven cortex (2019) (20)
Combining causal and similarity-based reasoning (2006) (19)
The logic of universalization guides moral judgment (2020) (19)
Human-Level Reinforcement Learning through Theory-Based Modeling, Exploration, and Planning (2021) (19)
Learning Structured Preferences (2010) (19)
Probabilistic internal physics models guide judgments about object dynamics (2011) (19)
Is Conditional Generative Modeling all you need for Decision-Making? (2022) (19)
Structured Correlation from the Causal Background (2008) (18)
ComPhy: Compositional Physical Reasoning of Objects and Events from Videos (2022) (18)
Learning Neural Acoustic Fields (2022) (18)
The acquisition of inductive constraints (2008) (18)
Physical problem solving: Joint planning with symbolic, geometric, and dynamic constraints (2017) (18)
Subjective randomness as statistical inference (2018) (17)
Representing Partial Programs with Blended Abstract Semantics (2020) (17)
Compositionality in rational analysis: grammar-based induction for concept learning (2008) (17)
At Human Speed: Deep Reinforcement Learning with Action Delay (2018) (17)
The Emergence of Organizing Structure in Conceptual Representation (2016) (17)
DiffSkill: Skill Abstraction from Differentiable Physics for Deformable Object Manipulations with Tools (2022) (17)
Learning Neuro-Symbolic Relational Transition Models for Bilevel Planning (2021) (17)
Efficient analysis-by-synthesis in vision : A computational framework , behavioral tests , and comparison with neural representations (2015) (16)
Sticking to the Evidence? A Behavioral and Computational Case Study of Micro-Theory Change in the Domain of Magnetism (2019) (16)
Program-Guided Image Manipulators (2019) (16)
DualSMC: Tunneling Differentiable Filtering and Planning under Continuous POMDPs (2019) (16)
Structured Representations of Utility in Combinatorial Domains (2017) (16)
Context-Sensitive Induction (2005) (16)
The Naïve Utility Calculus: Computational Principles Underlying Commonsense Psychology (Trends in Cognitive Sciences 20, 589–604; July 19, 2016) (2016) (16)
Wins above replacement: Responsibility attributions as counterfactual replacements (2014) (15)
Grounding Compositional Hypothesis Generation in Specific Instances (2018) (15)
Beyond Boolean logic: exploring representation languages for learning complex concepts (2010) (15)
Accurate Vision-based Manipulation through Contact Reasoning (2019) (15)
3DP3: 3D Scene Perception via Probabilistic Programming (2021) (15)
Exact and Approximate Sampling by Systematic Stochastic Search (2009) (15)
Bayesian collective learning emerges from heuristic social learning (2021) (15)
PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception (2021) (15)
Learning to learn generative programs with Memoised Wake-Sleep (2020) (14)
Deep Generative Vision as Approximate Bayesian Computation (2014) (14)
Blaming humans in autonomous vehicle accidents: Shared responsibility across levels of automation (2018) (14)
Edge replacement and nonindependence in causation (2010) (14)
Black boxes: Hypothesis testing via indirect perceptual evidence (2014) (14)
Modeling Human Performance on Statistical Word Segmentation Tasks (2007) (13)
The Role of Causal Models in Reasoning Under Uncertainty (2003) (13)
Grammar-based object representations in a scene parsing task (2009) (13)
The Infinite Latent Events Model (2009) (13)
Cross-Categorization : A Method for Discovering Multiple Overlapping Clusterings (2009) (13)
Some specifics about generalization (2001) (13)
Compositional Policy Priors (2013) (12)
Formal Approaches in Categorization: Nonparametric Bayesian models of categorization (2011) (12)
MOST-GAN: 3D Morphable StyleGAN for Disentangled Face Image Manipulation (2021) (12)
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Probabilistic Video Prediction From Noisy Data With a Posterior Confidence (2020) (12)
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Optimal Predictions in Everyday (2006) (12)
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ConceptFusion: Open-set Multimodal 3D Mapping (2023) (11)
Multi-Plane Program Induction with 3D Box Priors (2020) (11)
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Information Selection in Noisy Environments with Large Action Spaces (2014) (11)
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Responsibility judgments in voting scenarios (2015) (9)
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When Computer Vision Gazes at Cognition (2014) (9)
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Principles of Generalization for Learning Sequential Structure in Language (2008) (8)
The Development of Joint Belief-Desire Inferences (2012) (8)
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Emergent Collective Sensing in Human Groups (2015) (7)
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Risk and Regret of Hierarchical Bayesian Learners (2015) (7)
The Rational Basis of Representatives (2001) (7)
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Top-Down Synthesis for Library Learning (2022) (6)
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Dynamic Modeling of Hand-Object Interactions via Tactile Sensing (2021) (6)
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Building 3D Morphable Models from a Single Scan (2020) (5)
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Few-Shot Bayesian Imitation Learning with Logic over Programs (2019) (5)
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Evidence for an Intuitive Physics Engine in the Human Brain (2018) (5)
Categorization as Causal Explanation (2013) (5)
The Role of Causal Models in Statistical Reasoning (2003) (5)
Factorial Learning by Clustering Features (1994) (5)
Unsupervised Segmentation in Real-World Images via Spelke Object Inference (2022) (5)
Neurally-Guided Structure Inference (2019) (5)
Using Vocabulary Knowledge in Bayesian Multinomial Estimation (2001) (5)
Data and Analyses (2016) (4)
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Dimensionality Reduction via Program Induction (2015) (4)
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Grammar-Based Grounded Lexicon Learning (2022) (3)
3D Concept Grounding on Neural Fields (2022) (3)
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McGovern Institute for Brain Research (2005) (3)
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Error-Driven Stochastic Search for Theories and Concepts (2014) (3)
Intrinsically Motivated Exploration as Empowerment (2022) (3)
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Hypothesis-Space Constraints in Causal Learning (2015) (2)
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Temporal and Object Quantification Networks (2021) (2)
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Efficient Bayesian Inference for Nested Simulators (2019) (2)
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Probabilistic Models of Physical Reasoning (2020) (2)
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3D Concept Learning and Reasoning from Multi-View Images (2023) (1)
Non�?Parametric Bayesian Inference of Strategies in Repeated Games (2018) (1)
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Causal Structure in Conditional Reasoning (2004) (1)
Learning and using relational theories : supporting material (2007) (1)
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Building Theories of the World: Human and Machine Learning Perspectives (2008) (1)
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Subject Index to Volume 29 (1981) (1)
Mental Jenga: A counterfactual simulation model of physical support (2022) (1)
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Deep Reinforcement Learning with Temporal Abstraction and Intrinsic Motivation (2016) (1)
The Cognitive Architecture of Intentionality Perception: Animacy, Attention and Memory (2019) (1)
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Visual Dependency Transformers: Dependency Tree Emerges from Reversed Attention (2023) (1)
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Subjective probability in a nutshell (2006) (0)
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Perceiving unseen objects (2020) (0)
Forward Physics: How people learn and generalize novel dynamical models (2011) (0)
Arengiya Anyainya Aidmeniya Aburliya Adardiya Agngiya Aweniya Amaidya Abmarliya Awaadya Anguriya Adiaya Angeliya Algyeliya Adniadya Aleriya Umbaidya Anowadya Muriya Angenduriya Amburniya Andungiya Aneriya Aiyenga Undyaidya Gnaldena (2004) (0)
Modeling Social Common Sense for Seamless Human Machine Teaming: Inverting the Intuitive Game Engine with Probabilistic Programming (2017) (0)
Abstract knowledge guides search and prediction in novel situations (2009) (0)
Lucky or clever ? From changed expectations to responsibility judgments (2017) (0)
PDSketch: Integrated Domain Programming, Learning, and Planning (2022) (0)
Humans measure algorithmic complexity to guide engagement with event sequences (2020) (0)
Supplemental Material for 3DP3: 3D Scene Perception via Probabilistic Programming (2021) (0)
Edge replacement and nonindependence in causation - eScholarship (2010) (0)
Learning Rational Subgoals from Demonstrations and Instructions (2023) (0)
Big Data and Little Learners (2017) (0)
AAAI Press Formatting Instructions for Authors Using LaTeX -- A Guide (2021) (0)
Keep it Simple : Language Acquisition Without Complex Bayesian Models (2014) (0)
Multistability and Perceptual Inference Citation (2011) (0)
Modeling human planning in a life-like search-and-rescue mission (2021) (0)
One-shot Learning and Classification in Children (2017) (0)
Author response: Invariant representations of mass in the human brain (2019) (0)
Unsupervised Learning of Overlapping Concepts (2007) (0)
THEORY-BASED BAYESIAN MODELS OF INDUCTIVE INFERENCE Final Technical Report (2012) (0)
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics (2021) (0)
On the Expressiveness and Generalization of Hypergraph Neural Networks (2023) (0)
Questions for future research (2006) (0)
What are you looking at?: The acuity of joint attention (2014) (0)
Supplement for : Unsupervised Learning by Program Synthesis (2015) (0)
Tactile-Filter: Interactive Tactile Perception for Part Mating (2023) (0)
Inverting Audio-Visual Simulation for Shape and Material Perception (2018) (0)
Program ( Step II ) Lattice Search Condition Generation Attribute Search (2019) (0)
Inverse Rendering Best Explains Face Perception Under Extreme Illuminations (2020) (0)
Learning sequential patterns from graphical programs (2020) (0)
1. Not a Sure Thing: Fitness, Probability, and Causation Not a Sure Thing: Fitness, Probability, and Causation (pp. 147-171) (2010) (0)
34 Physical Object Repre sen ta tions for Perception and Cognition (2021) (0)
Probability, programs, and the mind: Building structured Bayesian models of cognition (2014) (0)
Probabilistic Programming Bots in Intuitive Physics Game Play (2021) (0)
A Unified Approach to Abductive Inference (2014) (0)
Physical p redictions over t ime (2013) (0)
Abstract Interpretation for Generalized Heuristic Search in Model-Based Planning (2022) (0)
Running head: ABSTRACT CAUSAL KNOWLEDGE The acquisition and use of abstract causal knowledge (2008) (0)
Xt-1 Yt-1 R Ot-1 Bt-1 At-1 Xt Yt Ot Bt At (2011) (0)
Elements of a stochastic 3 D prediction engine in larval zebrafish prey capture 1 2 (2019) (0)
What if everybody did that?: Universalization as a mechanism of moral decision-making (2019) (0)
PDSketch: Integrated Planning Domain Programming and Learning (2023) (0)
Interpreting Dynamic Scenes by a Physics Engine and Bottom-Up Visual Cues (2016) (0)
Planning with Sequence Models through Iterative Energy Minimization (2023) (0)
SUPPLEMENTARY MATERIAL FOR RISK AND REGRET OF HIERARCHICAL BAYESIAN LEARNERS (2015) (0)
Sticking to the evidence? A behavioral and computational case study of micro-theory change in the domain of magnetism. (2019) (0)
D ISCOVERING G ENERALIZABLE S PATIAL G OAL R EPRESENTATIONS VIA G RAPH - BASED A CTIVE R EWARD L EARNING (2022) (0)
Physical Inference for Object Perception in Complex Auditory Scenes (2018) (0)
Predicting object and scene descriptions with an information-theoretic model of pragmatics (2010) (0)
Strategies and representations in physical inference (2018) (0)
ynamic Causal Learning (2002) (0)
Abstract strategy learning underlies flexible transfer in physical problem solving (2020) (0)
Pre-registration - Gap Width (2017) (0)
Evidence that the Brain’s Physics Engine Runs Forward Simulations of What will Happen Next (2020) (0)
3D-IntPhys: Towards More Generalized 3D-grounded Visual Intuitive Physics under Challenging Scenes (2023) (0)
Formalizing accessibility using linguistic productivity (2017) (0)
Preprint prepared for ArXiv submission (2018) (0)
Compositional Visual Generation with Composable Diffusion Models Supplementary (2022) (0)
Solving the Baby Intuitions Benchmark with a Hierarchically Bayesian Theory of Mind (2022) (0)
Children's sensitivity to informant's inductive efficiency and learner's epistemic states in pedagogical contexts (2012) (0)

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