Sam J. Gershman
Affiliations: | Princeton University, Princeton, NJ | ||
| Psychology | Harvard University, Cambridge, MA, United States |
Area:
Cognitive & computational neuroscienceGoogle:
"Sam Gershman"Mean distance: 13.03 (cluster 23) | S | N | B | C | P |
Parents
Sign in to add mentor| 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 | |
Children
Sign in to add trainee| Hayley M. Dorfman | grad student | ||
| Edward H. Patzelt | grad student | ||
| Lucy Lai | grad student | 2018- | |
| Rahul Bhui | post-doc | Harvard | |
| Wouter Kool | post-doc | 2015- | Harvard |
| Honi Sanders | post-doc | 2016- | Harvard |
BETA: Related publications
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Publications
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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 |