Joshua B. Tenenbaum

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Thomas L. GriffithsProfessor of Psychology and Computer Science, Princeton UniversityE-mail confirmado em princeton.edu
Jiajun WuStanford UniversityE-mail confirmado em cs.stanford.edu
Noah D. GoodmanStanford UniversityE-mail confirmado em stanford.edu
Tomer UllmanAssistant Professor, HarvardE-mail confirmado em fas.harvard.edu
Antonio TorralbaProfessor of Computer Science, MITE-mail confirmado em csail.mit.edu
Charles KempMelbourne School of Psychological SciencesE-mail confirmado em unimelb.edu.au
William T. FreemanProfessor of Computer Science, MITE-mail confirmado em mit.edu
Vikash K. MansinghkaMIT, Probabilistic Computing ProjectE-mail confirmado em mit.edu
Samuel GershmanProfessor, Harvard UniversityE-mail confirmado em fas.harvard.edu
Kevin A SmithDepartment of Brain and Cognitive Sciences, MITE-mail confirmado em mit.edu
Chris BakerChief Scientist, ISEE AIE-mail confirmado em mit.edu
Brenden M. LakeAssociate Professor, New York UniversityE-mail confirmado em nyu.edu
Max Kleiman-WeinerUniversity of WashingtonE-mail confirmado em uw.edu
Armando Solar-LezamaMITE-mail confirmado em csail.mit.edu
Kelsey AllenResearch Scientist, DeepMindE-mail confirmado em deepmind.com
Tobias GerstenbergStanford UniversityE-mail confirmado em stanford.edu
Ruslan SalakhutdinovUPMC Professor, Machine Learning Department, CMUE-mail confirmado em cs.cmu.edu
Andrew PerforsUniversity of MelbourneE-mail confirmado em unimelb.edu.au
Ilker YildirimYale UniversityE-mail confirmado em yale.edu
Julian Jara-EttingerYale UniversityE-mail confirmado em yale.edu

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Joshua B. Tenenbaum

MIT

E-mail confirmado em mit.edu - Página inicial

Cognitive science artificial intelligence machine learning computational neuroscience cognitive psychology


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
A global geometric framework for nonlinear dimensionality reduction JB Tenenbaum, V Silva, JC Langford science 290 (5500), 2319-2323, 2000	17463	2000
Human-level concept learning through probabilistic program induction BM Lake, R Salakhutdinov, JB Tenenbaum Science 350 (6266), 1332-1338, 2015	3821	2015
Building machines that learn and think like people BM Lake, TD Ullman, JB Tenenbaum, SJ Gershman Behavioral and brain sciences 40, e253, 2017	3513	2017
Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling J Wu, C Zhang, T Xue, B Freeman, J Tenenbaum Advances in neural information processing systems 29, 2016	2422	2016
How to grow a mind: Statistics, structure, and abstraction JB Tenenbaum, C Kemp, TL Griffiths, ND Goodman Science 331 (6022), 1279-1285, 2011	2266	2011
The large‐scale structure of semantic networks: Statistical analyses and a model of semantic growth M Steyvers, JB Tenenbaum Cognitive science 29 (1), 41-78, 2005	1893	2005
Meta-learning for semi-supervised few-shot classification M Ren, E Triantafillou, S Ravi, J Snell, K Swersky, JB Tenenbaum, ... arXiv preprint arXiv:1803.00676, 2018	1753	2018
Hierarchical topic models and the nested Chinese restaurant process T Griffiths, M Jordan, J Tenenbaum, D Blei Advances in neural information processing systems 16, 2003	1593	2003
Hierarchical deep reinforcement learning: Integrating temporal abstraction and intrinsic motivation TD Kulkarni, K Narasimhan, A Saeedi, J Tenenbaum Advances in neural information processing systems 29, 2016	1529	2016
Topics in semantic representation. TL Griffiths, M Steyvers, JB Tenenbaum Psychological review 114 (2), 211, 2007	1481	2007
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022	1412	2022
Word learning as Bayesian inference. F Xu, JB Tenenbaum Psychological review 114 (2), 245, 2007	1382	2007
Global versus local methods in nonlinear dimensionality reduction V Silva, J Tenenbaum Advances in neural information processing systems 15, 2002	1295	2002
Machine behaviour I Rahwan, M Cebrian, N Obradovich, J Bongard, JF Bonnefon, C Breazeal, ... Nature 568 (7753), 477-486, 2019	1293	2019
Action understanding as inverse planning CL Baker, R Saxe, JB Tenenbaum Cognition 113 (3), 329-349, 2009	1223	2009
Causal inference in multisensory perception KP Körding, U Beierholm, WJ Ma, S Quartz, JB Tenenbaum, L Shams PLoS one 2 (9), e943, 2007	1218	2007
Theory-based Bayesian models of inductive learning and reasoning JB Tenenbaum, TL Griffiths, C Kemp Trends in cognitive sciences 10 (7), 309-318, 2006	1191	2006
Deep convolutional inverse graphics network TD Kulkarni, WF Whitney, P Kohli, J Tenenbaum Advances in neural information processing systems 28, 2015	1147	2015
Rethinking few-shot image classification: a good embedding is all you need? Y Tian, Y Wang, D Krishnan, JB Tenenbaum, P Isola Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020	1141	2020
One shot learning of simple visual concepts B Lake, R Salakhutdinov, J Gross, J Tenenbaum Proceedings of the annual meeting of the cognitive science society 33 (33), 2011	1102	2011

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