Tenenbaum, Joshua B.

The dynamics of memory as a consequence of optimal adaptation to a changing body

Kording, K. P., Tenenbaum, J. B., & Shadmehr, R. (2007) · Nature Neuroscience

Motor Control and AdaptationMemory and Neural Mechanisms

Cited by 393

Dissociating language and thought in large language models

Mahowald, K., Ivanova, A. A., Blank, I. A., Kanwisher, N., Tenenbaum, J. B., & Fedorenko, E. (2024) · Trends in Cognitive Sciences

Neurobiology of Language and BilingualismNatural Language Processing Techniques

Cited by 345

Compositional Visual Generation with Composable Diffusion Models

Liu, N., Li, S., Du, Y., Torralba, A., & Tenenbaum, J. B. (2022) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 295

ConceptGraphs: Open-Vocabulary 3D Scene Graphs for Perception and Planning

Gu, Q., Kuwajerwala, A., Morin, S., Jatavallabhula, K. M., Sen, B., Agarwal, A., Rivera, C., Paul, W., Ellis, K., Chellappa, R., et al. (2023) · arXiv

3D Shape Modeling and AnalysisRobot Manipulation and Learning

Cited by 289

Structured statistical models of inductive reasoning

Kemp, C., & Tenenbaum, J. B. (2009) · Psychological Review

Bayesian Modeling and Causal InferenceCategorization, perception, and language

Cited by 259

Mind games: Game engines as an architecture for intuitive physics

Ullman, T. D., Spelke, E., Battaglia, P., & Tenenbaum, J. B. (2017) · Trends in Cognitive Sciences

Child and Animal Learning DevelopmentSpatial Cognition and Navigation

Cited by 234

Ten-month-old infants infer the value of goals from the costs of actions

Liu, S., Ullman, T. D., Tenenbaum, J. B., & Spelke, E. S. (2017) · Science

Child and Animal Learning DevelopmentSocial Robot Interaction and HRI

Cited by 230

ConceptFusion: Open-set multimodal 3D mapping

Jatavallabhula, K., Kuwajerwala, A., Gu, Q., Omama, M., Iyer, G., Saryazdi, S., Chen, T., Maalouf, A., Li, S., Keetha, N., et al. (2023) · Robotics: Science and Systems XIX

Robotics and Sensor-Based LocalizationMultimodal Machine Learning Applications

Cited by 228

ConceptFusion: Open-set Multimodal 3D Mapping

Jatavallabhula, K. M., Kuwajerwala, A., Gu, Q., Omama, M., Chen, T., Maalouf, A., Li, S., Iyer, G., Saryazdi, S., Keetha, N., et al. (2023) · arXiv

Robotics and Sensor-Based LocalizationMultimodal Machine Learning Applications

Cited by 228

Secret Agents: Inferences About Hidden Causes by 10- and 12-Month-Old Infants

Saxe, R., Tenenbaum, J. B., & Carey, S. (2005) · Psychological Science

Child and Animal Learning DevelopmentSocial Robot Interaction and HRI

Cited by 210

The role of causality in judgment under uncertainty

Krynski, T. R., & Tenenbaum, J. B. (2007) · Journal of Experimental Psychology General

Bayesian Modeling and Causal InferenceDecision-Making and Behavioral Economics

Cited by 183

Multistability and perceptual inference

Gershman, S. J., Vul, E., & Tenenbaum, J. B. (2012) · Neural Computation

Visual perception and processing mechanismsNeural dynamics and brain function

Cited by 140

Planning with Diffusion for Flexible Behavior Synthesis

Janner, M., Du, Y., Tenenbaum, J. B., & Levine, S. (2022) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 140

DreamCoder: growing generalizable, interpretable knowledge with wake–sleep Bayesian program learning

Ellis, K., Wong, L., Nye, M., Sablé-Meyer, M., Cary, L., Anaya Pozo, L., Hewitt, L., Solar-Lezama, A., & Tenenbaum, J. B. (2023) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences

Evolutionary Algorithms and ApplicationsAI-based Problem Solving and Planning

Cited by 125

Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering

Sitzmann, V., Rezchikov, S., Freeman, W. T., Tenenbaum, J. B., & Durand, F. (2021) · arXiv

3D Shape Modeling and AnalysisComputer Graphics and Visualization Techniques

Cited by 117

Toward the neural implementation of structure learning

Tervo, D. G. R., Tenenbaum, J. B., & Gershman, S. J. (2016) · Current Opinion in Neurobiology

Bayesian Modeling and Causal InferenceMemory and Neural Mechanisms

Cited by 106

Rethink reporting of evaluation results in AI

Burnell, R., Schellaert, W., Burden, J., Ullman, T. D., Martinez-Plumed, F., Tenenbaum, J. B., Rutar, D., Cheke, L. G., Sohl-Dickstein, J., Mitchell, M., et al. (2023) · Science

Ethics and Social Impacts of AIScientific Computing and Data Management

Cited by 104

DreamCoder: bootstrapping inductive program synthesis with wake-sleep library learning

Ellis, K., Wong, C., Nye, M., Sablé-Meyer, M., Morales, L., Hewitt, L., Cary, L., Solar-Lezama, A., & Tenenbaum, J. B. (2021) · Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation

Evolutionary Algorithms and ApplicationsAI-based Problem Solving and Planning

Cited by 103

The logic of universalization guides moral judgment

Levine, S., Kleiman-Weiner, M., Schulz, L., Tenenbaum, J., & Cushman, F. (2020) · Proceedings of the National Academy of Sciences

Psychology of Moral and Emotional JudgmentEthics in Business and Education

Cited by 88

Dissociating language and thought in large language models

Mahowald, K., Ivanova, A. A., Blank, I. A., Kanwisher, N., Tenenbaum, J. B., & Fedorenko, E. (2023) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 80

A theory of learning to infer.

Dasgupta, I., Schulz, E., Tenenbaum, J. B., & Gershman, S. J. (2020) · Psychological Review

Bayesian Modeling and Causal InferenceDecision-Making and Behavioral Economics

Cited by 70

Is Conditional Generative Modeling all you need for Decision-Making?

Ajay, A., Du, Y., Gupta, A., Tenenbaum, J., Jaakkola, T., & Agrawal, P. (2022) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 61

LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers

Olausson, T., Gu, A., Lipkin, B., Zhang, C., Solar-Lezama, A., Tenenbaum, J., & Levy, R. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Logic, Reasoning, and KnowledgeTopic Modeling

Cited by 57

Building Cooperative Embodied Agents Modularly with Large Language Models

Zhang, H., Du, W., Shan, J., Zhou, Q., Du, Y., Tenenbaum, J. B., Shu, T., & Gan, C. (2023) · arXiv

Reinforcement Learning in RoboticsMulti-Agent Systems and Negotiation

Cited by 52