Tenenbaum, Joshua B.

A Global Geometric Framework for Nonlinear Dimensionality Reduction

Tenenbaum, J. B., Silva, V. D., & Langford, J. C. (2000) · Science

Face and Expression RecognitionTopological and Geometric Data Analysis

Cited by 13,585

Human-level concept learning through probabilistic program induction

Lake, B. M., Salakhutdinov, R., & Tenenbaum, J. B. (2015) · Science

Domain Adaptation and Few-Shot LearningBayesian Modeling and Causal Inference

Cited by 2,817

Building machines that learn and think like people

Lake, B. M., Ullman, T. D., Tenenbaum, J. B., & Gershman, S. J. (2017) · Behavioral and Brain Sciences

Psychiatry, Mental Health, NeuroscienceAI-based Problem Solving and Planning

Cited by 2,550

Building Machines That Learn and Think Like People

Lake, B. M., Ullman, T. D., Tenenbaum, J. B., & Gershman, S. J. (2016) · arXiv

Psychiatry, Mental Health, NeuroscienceAI-based Problem Solving and Planning

Cited by 2,550

How to grow a mind: Statistics, structure, and abstraction

Tenenbaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. D. (2011) · Science

Bayesian Modeling and Causal InferenceCategorization, perception, and language

Cited by 1,815

Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling

Wu, J., Zhang, C., Xue, T., Freeman, W. T., & Tenenbaum, J. B. (2016) · arXiv

3D Shape Modeling and AnalysisGenerative Adversarial Networks and Image Synthesis

Cited by 1,393

Machine behaviour

Rahwan, I., Cebrian, M., Obradovich, N., Bongard, J., Bonnefon, J.-F., Breazeal, C., Crandall, J. W., Christakis, N. A., Couzin, I. D., Jackson, M. O., et al. (2019) · Nature

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 1,364

Improving Factuality and Reasoning in Language Models through Multiagent Debate

Du, Y., Li, S., Torralba, A., Tenenbaum, J. B., & Mordatch, I. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1,202

Topics in semantic representation

Griffiths, T. L., Steyvers, M., & Tenenbaum, J. B. (2007) · Psychological Review

Topic ModelingNatural Language Processing Techniques

Cited by 1,122

Causal Inference in Multisensory Perception

Körding, K. P., Beierholm, U., Ma, W. J., Quartz, S., Tenenbaum, J. B., & Shams, L. (2007) · PLoS ONE

Multisensory perception and integrationVisual perception and processing mechanisms

Cited by 1,069

Rethinking Few-Shot Image Classification: A Good Embedding is All You Need?

Tian, Y., Wang, Y., Krishnan, D., Tenenbaum, J. B., & Isola, P. (2020) · Lecture Notes in Computer Science

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 952

Action understanding as inverse planning

Baker, C. L., Saxe, R., & Tenenbaum, J. B. (2009) · Cognition

Child and Animal Learning DevelopmentAction Observation and Synchronization

Cited by 920

Theory-based Bayesian models of inductive learning and reasoning

Tenenbaum, J. B., Griffiths, T. L., & Kemp, C. (2006) · Trends in Cognitive Sciences

Bayesian Modeling and Causal InferenceCategorization, perception, and language

Cited by 880

Separating Style and Content with Bilinear Models

Tenenbaum, J. B., & Freeman, W. T. (2000) · Neural Computation

Neural Networks and ApplicationsFace and Expression Recognition

Cited by 840

Simulation as an engine of physical scene understanding

Battaglia, P. W., Hamrick, J. B., & Tenenbaum, J. B. (2013) · Proceedings of the National Academy of Sciences

Visual perception and processing mechanismsBayesian Modeling and Causal Inference

Cited by 681

A critical period for second language acquisition: Evidence from 2/3 million English speakers

Hartshorne, J. K., Tenenbaum, J. B., & Pinker, S. (2018) · Cognition

Language Development and DisordersEFL/ESL Teaching and Learning

Cited by 625

Church: a language for generative models

Goodman, N., Mansinghka, V., Roy, D. M., Bonawitz, K., & Tenenbaum, J. B. (2012) · arXiv

Bayesian Modeling and Causal InferenceLogic, programming, and type systems

Cited by 577

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 569

Probabilistic models of cognition: exploring representations and inductive biases

Griffiths, T. L., Chater, N., Kemp, C., Perfors, A., & Tenenbaum, J. B. (2010) · Trends in Cognitive Sciences

Bayesian Modeling and Causal InferenceCognitive Science and Education Research

Cited by 568

The neural architecture of language: Integrative modeling converges on predictive processing

Schrimpf, M., Blank, I. A., Tuckute, G., Kauf, C., Hosseini, E. A., Kanwisher, N., Tenenbaum, J. B., & Fedorenko, E. (2021) · Proceedings of the National Academy of Sciences

Neurobiology of Language and BilingualismEmbodied and Extended Cognition

Cited by 517

Rational quantitative attribution of beliefs, desires and percepts in human mentalizing

Baker, C. L., Jara-Ettinger, J., Saxe, R., & Tenenbaum, J. B. (2017) · Nature Human Behaviour

Child and Animal Learning DevelopmentSocial Robot Interaction and HRI

Cited by 515

A rational analysis of rule-based concept learning

Goodman, N. D., Tenenbaum, J. B., Feldman, J., & Griffiths, T. L. (2008) · Cognitive Science

Categorization, perception, and languageBayesian Modeling and Causal Inference

Cited by 469

The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision

Mao, J., Gan, C., Kohli, P., Tenenbaum, J. B., & Wu, J. (2019) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 444

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. (2024) · 2024 IEEE International Conference on Robotics and Automation (ICRA)

3D Shape Modeling and AnalysisRobot Manipulation and Learning

Cited by 406