Samuel Gershman

引用次數

	全部	自 2019 年
引文	22613	17598
H 指數	73	69
i10 指數	160	158

3900

1950

975

2925

2011201220132014201520162017201820192020202120222023202469 156 256 349 510 687 1104 1660 2267 3358 3246 3663 3873 1168

公開取用

查看全部

149 篇文章

0 篇文章

可供使用

無法使用

根據資金強制性政策

共同作者

Joshua B. TenenbaumMIT在 mit.edu 的電子郵件地址已通過驗證
Yael NivProfessor of Psychology and Neuroscience, Princeton University在 princeton.edu 的電子郵件地址已通過驗證
Kenneth A. NormanProfessor of Psychology and Neuroscience, Princeton University在 princeton.edu 的電子郵件地址已通過驗證
Eric SchulzHelmholtz Munich在 helmholtz-munich.de 的電子郵件地址已通過驗證
Matthew BotvinickGoogle DeepMind, Yale Law School, University College London在 google.com 的電子郵件地址已通過驗證
Tomer UllmanAssistant Professor, Harvard在 fas.harvard.edu 的電子郵件地址已通過驗證
Nathaniel D. DawHuo Professor of Computational and Theoretical Neuroscience, Princeton University在 princeton.edu 的電子郵件地址已通過驗證
Fiery CushmanPsychology, Harvard University在 fas.harvard.edu 的電子郵件地址已通過驗證
David BleiProfessor of Statistics and Computer Science, Columbia University在 columbia.edu 的電子郵件地址已通過驗證
Kimberly Lauren StachenfeldResearch Scientist, Google DeepMind在 google.com 的電子郵件地址已通過驗證
Naoshige UchidaProfessor of Molecular and Cellular Biology, Harvard University在 mcb.harvard.edu 的電子郵件地址已通過驗證
Rahul BhuiMassachusetts Institute of Technology在 mit.edu 的電子郵件地址已通過驗證
Wouter KoolAssistant Professor at Washington University in St. Louis在 wustl.edu 的電子郵件地址已通過驗證
Ishita DasguptaSenior Research Scientist, DeepMind在 google.com 的電子郵件地址已通過驗證
Noah D. GoodmanStanford University在 stanford.edu 的電子郵件地址已通過驗證
Brenden M. LakeAssistant Professor, New York University在 nyu.edu 的電子郵件地址已通過驗證
John G. MikhaelHarvard在 hms.harvard.edu 的電子郵件地址已通過驗證
Momchil S. TomovHarvard University在 g.harvard.edu 的電子郵件地址已通過驗證
Marie MonfilsProfessor; The University of Texas at Austin在 utexas.edu 的電子郵件地址已通過驗證
Lucy LaiPh.D. Candidate, Harvard University在 g.harvard.edu 的電子郵件地址已通過驗證

追蹤

Samuel Gershman

Professor, Harvard University

在 fas.harvard.edu 的電子郵件地址已通過驗證 - 首頁

Computational neuroscience cognitive science machine learning


標題按引用次數排序按年份排序按標題排序	引用次數引用次數	年份
Building machines that learn and think like people BM Lake, TD Ullman, JB Tenenbaum, SJ Gershman Behavioral and brain sciences 40, e253, 2017	2976	2017
Model-based influences on humans' choices and striatal prediction errors ND Daw, SJ Gershman, B Seymour, P Dayan, RJ Dolan Neuron 69 (6), 1204-1215, 2011	1870	2011
The hippocampus as a predictive map KL Stachenfeld, MM Botvinick, SJ Gershman Nature Neuroscience 20, 1643-1653, 2017	833	2017
Computational rationality: A converging paradigm for intelligence in brains, minds, and machines SJ Gershman, EJ Horvitz, JB Tenenbaum Science 349 (6245), 273-278, 2015	761	2015
A tutorial on Bayesian nonparametric models SJ Gershman, DM Blei Journal of Mathematical Psychology 56, 1-12, 2012	715	2012
Reinforcement learning and episodic memory in humans and animals: an integrative framework SJ Gershman, ND Daw Annual review of psychology 68, 101-128, 2017	495	2017
Context, learning, and extinction SJ Gershman, DM Blei, Y Niv Psychological Review 117 (1), 197-209, 2010	420	2010
The successor representation in human reinforcement learning I Momennejad, EM Russek, JH Cheong, MM Botvinick, ND Daw, ... Nature human behaviour 1 (9), 680-692, 2017	414	2017
Reinforcement learning in multidimensional environments relies on attention mechanisms Y Niv, R Daniel, A Geana, SJ Gershman, YC Leong, A Radulescu, ... Journal of Neuroscience 35 (21), 8145-8157, 2015	386	2015
The curse of planning: Dissecting multiple reinforcement learning systems by taxing the central executive AR Otto, SJ Gershman, AB Markman, ND Daw Psychological Science 24 (5), 751-761, 2013	374	2013
Amortized Inference in Probabilistic Reasoning SJ Gershman, ND Goodman Proceedings of the 36th Annual Cognitive Science Society, 2013	370	2013
Toward a universal decoder of linguistic meaning from brain activation F Pereira, B Lou, B Pritchett, S Ritter, SJ Gershman, N Kanwisher, ... Nature communications 9 (1), 963, 2018	328	2018
Predictive representations can link model-based reinforcement learning to model-free mechanisms EM Russek, I Momennejad, MM Botvinick, SJ Gershman, ND Daw PLoS computational biology 13 (9), e1005768, 2017	326	2017
Learning latent structure: carving nature at its joints SJ Gershman, Y Niv Current Opinion in Neurobiology 20 (2), 251-256, 2010	317	2010
Retrospective revaluation in sequential decision making: A tale of two systems SJ Gershman, AB Markman, AR Otto Journal of Experimental Psychology: General 143, 182-194, 2014	289	2014
Interplay of approximate planning strategies QJM Huys, N Lally, P Faulkner, N Eshel, E Seifritz, SJ Gershman, ... Proceedings of the National Academy of Sciences 112 (10), 3098-3103, 2015	281	2015
Cost-benefit arbitration between multiple reinforcement-learning systems W Kool, SJ Gershman, FA Cushman Psychological science 28 (9), 1321-1333, 2017	263	2017
Deep successor reinforcement learning TD Kulkarni, A Saeedi, S Gautam, SJ Gershman arXiv preprint arXiv:1606.02396, 2016	242	2016
Deconstructing the human algorithms for exploration SJ Gershman Cognition 173, 34-42, 2018	231	2018
The successor representation: its computational logic and neural substrates SJ Gershman Journal of Neuroscience 38 (33), 7193-7200, 2018	203	2018

系統目前無法執行作業，請稍後再試。

文章 1–20

每年的引文數

重複引用

合併引文

新增共同作者共同作者

追蹤

引用次數

共同作者