Joshua B. Tenenbaum

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Thomas L. GriffithsProfessor of Psychology and Computer Science, Princeton UniversityAdresse e-mail validée de princeton.edu
Jiajun WuStanford UniversityAdresse e-mail validée de cs.stanford.edu
Noah D. GoodmanStanford UniversityAdresse e-mail validée de stanford.edu
Tomer UllmanAssistant Professor, HarvardAdresse e-mail validée de fas.harvard.edu
Antonio TorralbaProfessor of Computer Science, MITAdresse e-mail validée de csail.mit.edu
Charles KempMelbourne School of Psychological SciencesAdresse e-mail validée de unimelb.edu.au
William T. FreemanProfessor of Computer Science, MITAdresse e-mail validée de mit.edu
Vikash K. MansinghkaMIT, Probabilistic Computing ProjectAdresse e-mail validée de mit.edu
Samuel GershmanProfessor, Harvard UniversityAdresse e-mail validée de fas.harvard.edu
Kevin A SmithDepartment of Brain and Cognitive Sciences, MITAdresse e-mail validée de mit.edu
Chris BakerChief Scientist, ISEE AIAdresse e-mail validée de mit.edu
Brenden M. LakeAssociate Professor, New York UniversityAdresse e-mail validée de nyu.edu
Max Kleiman-WeinerUniversity of WashingtonAdresse e-mail validée de uw.edu
Armando Solar-LezamaMITAdresse e-mail validée de csail.mit.edu
Kelsey AllenResearch Scientist, DeepMindAdresse e-mail validée de deepmind.com
Tobias GerstenbergStanford UniversityAdresse e-mail validée de stanford.edu
Ruslan SalakhutdinovUPMC Professor, Machine Learning Department, CMUAdresse e-mail validée de cs.cmu.edu
Andrew PerforsUniversity of MelbourneAdresse e-mail validée de unimelb.edu.au
Mark SteyversUniversity of California, IrvineAdresse e-mail validée de uci.edu
Julian Jara-EttingerYale UniversityAdresse e-mail validée de yale.edu

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Joshua B. Tenenbaum

MIT

Adresse e-mail validée de mit.edu - Page d'accueil

Cognitive science artificial intelligence machine learning computational neuroscience cognitive psychology


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
A global geometric framework for nonlinear dimensionality reduction JB Tenenbaum, V Silva, JC Langford science 290 (5500), 2319-2323, 2000	17369	2000
Human-level concept learning through probabilistic program induction BM Lake, R Salakhutdinov, JB Tenenbaum Science 350 (6266), 1332-1338, 2015	3796	2015
Building machines that learn and think like people BM Lake, TD Ullman, JB Tenenbaum, SJ Gershman Behavioral and brain sciences 40, e253, 2017	3412	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	2403	2016
How to grow a mind: Statistics, structure, and abstraction JB Tenenbaum, C Kemp, TL Griffiths, ND Goodman Science 331 (6022), 1279-1285, 2011	2233	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	1894	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	1714	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	1590	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	1497	2016
Topics in semantic representation. TL Griffiths, M Steyvers, JB Tenenbaum Psychological review 114 (2), 211, 2007	1479	2007
Word learning as Bayesian inference. F Xu, JB Tenenbaum Psychological review 114 (2), 245, 2007	1382	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	1291	2022
Global versus local methods in nonlinear dimensionality reduction V Silva, J Tenenbaum Advances in neural information processing systems 15, 2002	1285	2002
Machine behaviour I Rahwan, M Cebrian, N Obradovich, J Bongard, JF Bonnefon, C Breazeal, ... Nature 568 (7753), 477-486, 2019	1246	2019
Action understanding as inverse planning CL Baker, R Saxe, JB Tenenbaum Cognition 113 (3), 329-349, 2009	1217	2009
Causal inference in multisensory perception KP Körding, U Beierholm, WJ Ma, S Quartz, JB Tenenbaum, L Shams PLoS one 2 (9), e943, 2007	1200	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	1182	2006
Deep convolutional inverse graphics network TD Kulkarni, WF Whitney, P Kohli, J Tenenbaum Advances in neural information processing systems 28, 2015	1145	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	1120	2020
Separating style and content with bilinear models JB Tenenbaum, WT Freeman Neural Computation 12 (6), 1247-1283, 2000	1097	2000

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