Brenden Lake - Google Scholar

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Joshua B. TenenbaumMITVerified email at mit.edu
Ruslan SalakhutdinovUPMC Professor, Machine Learning Department, CMUVerified email at cs.cmu.edu
Tomer UllmanAssistant Professor, HarvardVerified email at fas.harvard.edu
Samuel GershmanAssociate Professor, Harvard UniversityVerified email at fas.harvard.edu
Marco BaroniICREA Professor (Barcelona) and FAIR Research Scientist (Paris)Verified email at fb.com
Todd GureckisProfessor of Psychology, New York UniversityVerified email at nyu.edu
Jason GrossGraduate, Massachusetts Institute of TechnologyVerified email at mit.edu
Anselm RotheNew York UniversityVerified email at nyu.edu
James L. McClellandStanford UniversityVerified email at stanford.edu
Reuben FeinmanNew York UniversityVerified email at nyu.edu
Wojciech ZarembaCo-Founder of OpenAIVerified email at openai.com
Rob FergusResearch Scientist, DeepMind. Professor of Computer Science, New York UniversityVerified email at cs.nyu.edu
Chia-ying (Jackie) LeeGraduate student of Computer Science, MITVerified email at csail.mit.edu
James GlassMIT Computer Science and Artificial Intelligence LaboratoryVerified email at mit.edu
Tal LinzenJohns Hopkins UniversityVerified email at jhu.edu
Brian D ZiebartAssociate Professor of Computer Science, University of Illinois at ChicagoVerified email at uic.edu
Mathew MonfortMassachusetts Institute of Technology (MIT)Verified email at mit.edu
Gautam VallabhaTechnical Staff, Johns Hopkins University Applied Physics LaboratoryVerified email at jhuapl.edu
Kanishk GandhiNew York UniversityVerified email at nyu.edu
Neil D. LawrenceUniversity of CambridgeVerified email at cl.cam.ac.uk

Brenden Lake

Assistant Professor of Psychology and Data Science, New York University

Verified email at nyu.edu - Homepage

cognitive science data science artificial intelligence machine learning cognitive psychology


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Human-level concept learning through probabilistic program induction BM Lake, R Salakhutdinov, JB Tenenbaum Science 350 (6266), 1332-1338, 2015	1474	2015
Building machines that learn and think like people BM Lake, TD Ullman, JB Tenenbaum, SJ Gershman Behavioral and Brain Sciences 40, 2017	1065	2017
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	387	2011
One-shot learning by inverting a compositional causal process BM Lake, RR Salakhutdinov, J Tenenbaum Advances in neural information processing systems, 2526-2534, 2013	166	2013
Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networks BM Lake, M Baroni International Conference on Machine Learning (ICML), 2018	159*	2018
Discovering structure by learning sparse graphs B Lake, J Tenenbaum Proceedings of the 33rd Annual Cognitive Science Conference, 2010	100	2010
Deep Neural Networks Predict Category Typicality Ratings for Images BM Lake, W Zaremba, R Fergus, TM Gureckis Proceedings of the 37th Annual Conference of the Cognitive Science Society, 2015	47	2015
Rearranging the familiar: Testing compositional generalization in recurrent networks J Loula, M Baroni, BM Lake arXiv preprint arXiv:1807.07545, 2018	42	2018
One-shot learning of generative speech concepts BM Lake, C Lee, JR Glass, JB Tenenbaum Proceedings of the 36th Annual Meeting of the Cognitive Science Soceity, 803–808, 2014	36	2014
Human few-shot learning of compositional instructions BM Lake, T Linzen, M Baroni Proceedings of the 41st Annual Conference of the Cognitive Science Society, 2019	30	2019
The Omniglot challenge: a 3-year progress report BM Lake, R Salakhutdinov, JB Tenenbaum Current Opinion in Behavioral Sciences 29, 97-104, 2019	24	2019
Compositional generalization through meta sequence-to-sequence learning BM Lake Advances in Neural Information Processing Systems, 2019	23	2019
Question asking as program generation A Rothe, BM Lake, T Gureckis Advances in neural information processing systems, 1046-1055, 2017	23	2017
Modeling unsupervised perceptual category learning BM Lake, GK Vallabha, JL McClelland IEEE Transactions on Autonomous Mental Development 1 (1), 35-43, 2009	22	2009
Towards more human-like concept learning in machines: Compositionality, causality, and learning-to-learn B Lake Massachusetts Institute of Technology, 2014	21	2014
Concept learning as motor program induction: A large-scale empirical study B Lake, R Salakhutdinov, J Tenenbaum Proceedings of the Annual Meeting of the Cognitive Science Society 34 (34), 2012	20	2012
Estimating the strength of unlabeled information during semi-supervised learning B Lake, J McClelland Proceedings of the Annual Meeting of the Cognitive Science Society 33 (33), 2011	15	2011
Asking and evaluating natural language questions A Rothe, BM Lake, TM Gureckis Proceedings of the 38th Annual Conference of the Cognitive Science Society, 2016	12	2016
The emergence of organizing structure in conceptual representation BM Lake, ND Lawrence, JB Tenenbaum Cognitive science 42, 809-832, 2018	10	2018
Learning Inductive Biases with Simple Neural Networks R Feinman, BM Lake Proceedings of the 40th Annual Conference of the Cognitive Science Society, 2018	10	2018

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