Sam J. Gershman

Princeton University, Princeton, NJ 
 Psychology Harvard University, Cambridge, MA, United States 
Cognitive & computational neuroscience
"Sam Gershman"
Mean distance: 13.03 (cluster 23)


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Ken A. Paller research assistant 2004-2005 Northwestern
Hedy Kober research assistant 2005-2007 Columbia
Kevin Nicholas Ochsner research assistant 2005-2007 Columbia
Tor D. Wager research assistant 2005-2007 Columbia
Yael Niv grad student 2013 Princeton
 (Memory modification in the brain: Computational and experimental investigations.)
Kenneth A. Norman grad student 2013 Princeton
 (Memory modification in the brain: Computational and experimental investigations.)
Joshua Tenenbaum post-doc MIT
Nathaniel D. Daw research scientist 2007-2008 NYU
Bijan Pesaran research scientist 2007-2008 NYU


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Zhenglong Zhou research assistant 2018-2019
Hayley M. Dorfman grad student
Edward H. Patzelt grad student
Lucy Lai grad student 2018-
Rahul Bhui post-doc Harvard
Honi Sanders post-doc 2016- Harvard
Wouter Kool post-doc 2015-2019 Harvard
Prashant C. Raju research scientist 2020- Harvard
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Gershman SJ. (2016) On the Blessing of Abstraction. Quarterly Journal of Experimental Psychology (2006). 1-9
Tervo DG, Tenenbaum JB, Gershman SJ. (2016) Toward the neural implementation of structure learning. Current Opinion in Neurobiology. 37: 99-105
Gershman SJ. (2015) A Unifying Probabilistic View of Associative Learning. Plos Computational Biology. 11: e1004567
Gershman SJ, Frazier PI, Blei DM. (2015) Distance Dependent Infinite Latent Feature Models. Ieee Transactions On Pattern Analysis and Machine Intelligence. 37: 334-45
Gershman SJ, Horvitz EJ, Tenenbaum JB. (2015) Computational rationality: A converging paradigm for intelligence in brains, minds, and machines. Science (New York, N.Y.). 349: 273-8
Gershman SJ, Hartley CA. (2015) Individual differences in learning predict the return of fear. Learning & Behavior. 43: 243-50
Niv Y, Daniel R, Geana A, et al. (2015) Reinforcement learning in multidimensional environments relies on attention mechanisms. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 35: 8145-57
Gershman SJ, Tenenbaum JB, Jäkel F. (2015) Discovering hierarchical motion structure. Vision Research
Gershman SJ, Niv Y. (2015) Novelty and Inductive Generalization in Human Reinforcement Learning. Topics in Cognitive Science
Huys QJ, Lally N, Faulkner P, et al. (2015) Interplay of approximate planning strategies. Proceedings of the National Academy of Sciences of the United States of America. 112: 3098-103
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