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ORCIDSamuel Gershman
Sam Gershman – Samuel J. Gershman
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- affiliation: MIT, Cambridge, USA
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2020 – today
- 2024
[j33]Samuel J. Gershman:
What have we learned about artificial intelligence from studying the brain? Biol. Cybern. 118(1-2): 1-5 (2024)- [j32]Alicia M. Chen
, Andrew Palacci, Natalia Vélez, Robert D. Hawkins, Samuel J. Gershman:
A Hierarchical Bayesian Model of Adaptive Teaching. Cogn. Sci. 48(7) (2024) - [j31]Rick Dale, Ruth M. J. Byrne, Emma Cohen, Ophelia Deroy, Samuel J. Gershman, Janet H. Hsiao, Ping Li, Padraic Monaghan, David C. Noelle, Iris van Rooij, Priti Shah, Michael J. Spivey, Sashank Varma:
Introduction to Progress and Puzzles of Cognitive Science. Cogn. Sci. 48(7) (2024) - [c36]Tanishq Kumar, Blake Bordelon, Samuel J. Gershman, Cengiz Pehlevan:
Grokking as the transition from lazy to rich training dynamics. ICLR 2024 - [i21]Wilka Carvalho, Momchil S. Tomov, William de Cothi, Caswell Barry, Samuel J. Gershman:
Predictive representations: building blocks of intelligence. CoRR abs/2402.06590 (2024) - [i20]Ruairidh M. Battleday, Samuel J. Gershman:
Artificial intelligence for science: The easy and hard problems. CoRR abs/2408.14508 (2024) - 2023
- [j30]Samuel J. Gershman:
The molecular memory code and synaptic plasticity: A synthesis. Biosyst. 224: 104825 (2023) - [j29]Haoxue Fan, Taylor Burke, Deshawn Chatman Sambrano, Emily Dial, Elizabeth A. Phelps, Samuel J. Gershman:
Pupil Size Encodes Uncertainty during Exploration. J. Cogn. Neurosci. 35(9): 1508-1520 (2023) - [j28]Jay A. Hennig, Sandra A. Romero Pinto, Takahiro Yamaguchi, Scott W. Linderman, Naoshige Uchida, Samuel J. Gershman:
Emergence of belief-like representations through reinforcement learning. PLoS Comput. Biol. 19(9) (2023) - [c35]Reed Orchinik, Rachit Dubey, Samuel Gershman, Derek Powell, Rahul Bhui:
Learning About Scientists from Climate Consensus Messaging. CogSci 2023 - [c34]Younes Strittmatter, Markus Spitzer, Miguel Ruiz-Garcia, Samuel Gershman, Sebastian Musslick:
Does a Curriculum Improve Perceptual Decision Making? CogSci 2023 - [c33]Changmin Yu, Neil Burgess, Maneesh Sahani, Samuel J. Gershman:
Successor-Predecessor Intrinsic Exploration. NeurIPS 2023 - [i19]Changmin Yu, Neil Burgess, Maneesh Sahani, Sam Gershman:
Successor-Predecessor Intrinsic Exploration. CoRR abs/2305.15277 (2023) - [i18]Tanishq Kumar, Blake Bordelon, Samuel J. Gershman, Cengiz Pehlevan:
Grokking as the Transition from Lazy to Rich Training Dynamics. CoRR abs/2310.06110 (2023) - [i17]Marcel Binz, Stephan Alaniz, Adina Roskies, Balazs Aczel, Carl T. Bergstrom, Colin Allen, Daniel Schad, Dirk Wulff, Jevin D. West, Qiong Zhang, Richard M. Shiffrin, Samuel J. Gershman, Ven Popov, Emily M. Bender, Marco Marelli, Matthew M. Botvinick, Zeynep Akata, Eric Schulz:
How should the advent of large language models affect the practice of science? CoRR abs/2312.03759 (2023) - [i16]Qihong Lu, Tan T. Nguyen, Qiong Zhang, Uri Hasson, Thomas L. Griffiths, Jeffrey M. Zacks, Samuel J. Gershman, Kenneth A. Norman:
Toward a More Biologically Plausible Neural Network Model of Latent Cause Inference. CoRR abs/2312.08519 (2023) - 2022
- [j27]Daniel C. McNamee, Kimberly L. Stachenfeld, Matthew M. Botvinick, Samuel J. Gershman:
Compositional Sequence Generation in the Entorhinal-Hippocampal System. Entropy 24(12): 1791 (2022) - [c32]Christopher Bates, Samuel Gershman:
Coding Strategies in Memory for 3D Objects: The Influence of Task Uncertainty. CogSci 2022 - [c31]Felix A. Sosa, Samuel Gershman, Tomer D. Ullman:
Combining mental simulation and abstract reasoning explains people's reaction time in an intuitive physics task. CogSci 2022 - [c30]Tuan Anh Le, Katherine M. Collins, Luke Hewitt, Kevin Ellis, Siddharth Narayanaswamy, Samuel Gershman, Joshua B. Tenenbaum:
Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface. ICLR 2022 - 2021
- [j26]Thomas Pouncy, Pedro Tsividis, Samuel J. Gershman:
What Is the Model in Model-Based Planning? Cogn. Sci. 45(1) (2021) - [j25]Samuel J. Gershman, Marc Guitart-Masip, James F. Cavanagh:
Neural signatures of arbitration between Pavlovian and instrumental action selection. PLoS Comput. Biol. 17(2) (2021) - [j24]John G. Mikhael, Lucy Lai, Samuel J. Gershman:
Rational inattention and tonic dopamine. PLoS Comput. Biol. 17(3) (2021) - [c29]Ruocheng Wang, Jiayuan Mao, Samuel Gershman, Jiajun Wu:
Language-Mediated, Object-Centric Representation Learning. ACL/IJCNLP (Findings) 2021: 2033-2046 - [c28]Nikhil X. Bhattasali, Momchil S. Tomov, Samuel J. Gershman:
CCNLab: A Benchmarking Framework for Computational Cognitive Neuroscience. NeurIPS Datasets and Benchmarks 2021 - [i15]Tuan Anh Le, Katherine M. Collins, Luke Hewitt, Kevin Ellis, N. Siddharth, Samuel J. Gershman, Joshua B. Tenenbaum:
Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface. CoRR abs/2107.06393 (2021) - [i14]Pedro A. Tsividis, João Loula, Jake Burga, Nathan Foss, Andres Campero, Thomas Pouncy, Samuel J. Gershman, Joshua B. Tenenbaum:
Human-Level Reinforcement Learning through Theory-Based Modeling, Exploration, and Planning. CoRR abs/2107.12544 (2021) - 2020
- [j23]Ishita Dasgupta, Demi Guo, Samuel J. Gershman, Noah D. Goodman:
Analyzing Machine-Learned Representations: A Natural Language Case Study. Cogn. Sci. 44(12) (2020) - [j22]Momchil S. Tomov, Samyukta Yagati, Agni Kumar, Wanqian Yang, Samuel J. Gershman:
Discovery of hierarchical representations for efficient planning. PLoS Comput. Biol. 16(4) (2020) - [c27]Max Kleiman-Weiner, Felix Sosa, Bill Thompson, Sebastiaan van Opheusden, Tom Griffiths, Samuel Gershman, Fiery Cushman:
Downloading Culture.zip: Social learning by program induction. CogSci 2020 - [i13]Ruocheng Wang, Jiayuan Mao, Samuel J. Gershman, Jiajun Wu:
Language-Mediated, Object-Centric Representation Learning. CoRR abs/2012.15814 (2020)
2010 – 2019
- 2019
- [j21]Samuel J. Gershman:
The Generative Adversarial Brain. Frontiers Artif. Intell. 2: 18 (2019) - [j20]Zoran Tiganj, Samuel J. Gershman, Per B. Sederberg, Marc W. Howard:
Estimating Scale-Invariant Future in Continuous Time. Neural Comput. 31(4) (2019) - [j19]Fiery Cushman, Samuel Gershman:
Editors' Introduction: Computational Approaches to Social Cognition. Top. Cogn. Sci. 11(2): 281-298 (2019) - [c26]Shari Liu, Fiery Cushman, Samuel Gershman, Wouter Kool, Elizabeth S. Spelke:
Hard choices: Children's understanding of the cost of action selection. CogSci 2019: 671-6677 - [c25]Charley M. Wu, Eric Schulz, Samuel Gershman:
Generalization as diffusion: human function learning on graphs. CogSci 2019: 3122-3128 - [c24]Max Kleiman-Weiner, Felix Sosa, Samuel Gershman, Fiery Cushman:
Downloading Culture.zip: Social learning by program induction with execution traces. CogSci 2019: 3495 - [c23]Isaac Lage, Emily Chen, Jeffrey He, Menaka Narayanan, Been Kim, Samuel J. Gershman, Finale Doshi-Velez:
Human Evaluation of Models Built for Interpretability. HCOMP 2019: 59-67 - [i12]Isaac Lage, Emily Chen, Jeffrey He, Menaka Narayanan, Been Kim, Sam Gershman, Finale Doshi-Velez:
An Evaluation of the Human-Interpretability of Explanation. CoRR abs/1902.00006 (2019) - [i11]Ishita Dasgupta, Demi Guo, Samuel J. Gershman, Noah D. Goodman:
Analyzing machine-learned representations: A natural language case study. CoRR abs/1909.05885 (2019) - 2018
- [j18]Wouter Kool, Samuel J. Gershman, Fiery Cushman:
Planning Complexity Registers as a Cost in Metacontrol. J. Cogn. Neurosci. 30(10) (2018) - [j17]Alexander J. Millner, Samuel J. Gershman, Matthew K. Nock, Hanneke E. M. den Ouden:
Pavlovian Control of Escape and Avoidance. J. Cogn. Neurosci. 30(10) (2018) - [c22]Christiane Baumann, Henrik Singmann, Vassilios E. Kaxiras, Samuel Gershman, Bettina von Helversen:
Explaining Human Decision Making in Optimal Stopping Tasks. CogSci 2018 - [c21]Ishita Dasgupta, Demi Guo, Andreas Stuhlmüller, Samuel Gershman, Noah D. Goodman:
Evaluating Compositionality in Sentence Embeddings. CogSci 2018 - [c20]Ishita Dasgupta, Kevin A. Smith, Eric Schulz, Josh Tenenbaum, Samuel Gershman:
Learning to act by integrating mental simulations and physical experiments. CogSci 2018 - [c19]Felix Sosa, Tomer D. Ullman, Samuel Gershman, Josh Tenenbaum, Tobias Gerstenberg:
Moral Dynamics: A Computational Model of Moral Judgment. CogSci 2018 - [c18]Isaac Lage, Andrew Slavin Ross, Samuel J. Gershman, Been Kim, Finale Doshi-Velez:
Human-in-the-Loop Interpretability Prior. NeurIPS 2018: 10180-10189 - [i10]Menaka Narayanan, Emily Chen, Jeffrey He, Been Kim, Sam Gershman, Finale Doshi-Velez:
How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation. CoRR abs/1802.00682 (2018) - [i9]Ishita Dasgupta, Demi Guo, Andreas Stuhlmüller, Samuel J. Gershman, Noah D. Goodman:
Evaluating Compositionality in Sentence Embeddings. CoRR abs/1802.04302 (2018) - [i8]Zoran Tiganj, Samuel J. Gershman, Per B. Sederberg, Marc W. Howard:
Estimating scale-invariant future in continuous time. CoRR abs/1802.06426 (2018) - [i7]Isaac Lage, Andrew Slavin Ross, Been Kim, Samuel J. Gershman, Finale Doshi-Velez:
Human-in-the-Loop Interpretability Prior. CoRR abs/1805.11571 (2018) - 2017
- [j16]Ardavan Saeedi, Tejas D. Kulkarni, Vikash K. Mansinghka, Samuel J. Gershman:
Variational Particle Approximations. J. Mach. Learn. Res. 18: 69:1-69:29 (2017) - [j15]Samuel J. Gershman, Jimmy Zhou, Cody Kommers:
Imaginative Reinforcement Learning: Computational Principles and Neural Mechanisms. J. Cogn. Neurosci. 29(12) (2017) - [j14]Samuel J. Gershman:
Dopamine, Inference, and Uncertainty. Neural Comput. 29(12) (2017) - [j13]Evan M. Russek, Ida Momennejad, Matthew M. Botvinick, Samuel J. Gershman, Nathaniel D. Daw:
Predictive representations can link model-based reinforcement learning to model-free mechanisms. PLoS Comput. Biol. 13(9) (2017) - [c17]Pedro Tsividis, Thomas Pouncy, Jaqueline L. Xu, Joshua B. Tenenbaum, Samuel J. Gershman:
Human Learning in Atari. AAAI Spring Symposia 2017 - [c16]Ishita Dasgupta, Eric Schulz, Noah D. Goodman, Samuel J. Gershman:
Amortized Hypothesis Generation. CogSci 2017 - [i6]Finale Doshi-Velez, Mason Kortz, Ryan Budish, Chris Bavitz, Sam Gershman, David O'Brien, Stuart Schieber, James Waldo, David Weinberger, Alexandra Wood:
Accountability of AI Under the Law: The Role of Explanation. CoRR abs/1711.01134 (2017) - 2016
- [j12]Wouter Kool, Fiery Cushman, Samuel J. Gershman:
When Does Model-Based Control Pay Off? PLoS Comput. Biol. 12(8) (2016) - [c15]Kayhan N. Batmanghelich, Ardavan Saeedi, Karthik Narasimhan, Samuel Gershman:
Nonparametric Spherical Topic Modeling with Word Embeddings. ACL (2) 2016 - [c14]Tomer D. Ullman, Max H. Siegel, Josh Tenenbaum, Samuel Gershman:
Coalescing the Vapors of Human Experience into a Viable and Meaningful Comprehension. CogSci 2016 - [c13]Eric Schulz, Josh Tenenbaum, David Duvenaud, Maarten Speekenbrink, Samuel J. Gershman:
Probing the Compositionality of Intuitive Functions. NIPS 2016: 3729-3737 - [i5]Kayhan N. Batmanghelich, Ardavan Saeedi, Karthik Narasimhan, Samuel Gershman:
Nonparametric Spherical Topic Modeling with Word Embeddings. CoRR abs/1604.00126 (2016) - [i4]Brenden M. Lake, Tomer D. Ullman, Joshua B. Tenenbaum, Samuel J. Gershman:
Building Machines That Learn and Think Like People. CoRR abs/1604.00289 (2016) - [i3]Tejas D. Kulkarni, Ardavan Saeedi, Simanta Gautam, Samuel J. Gershman:
Deep Successor Reinforcement Learning. CoRR abs/1606.02396 (2016) - 2015
- [j11]Samuel Gershman, Peter I. Frazier, David M. Blei:
Distance Dependent Infinite Latent Feature Models. IEEE Trans. Pattern Anal. Mach. Intell. 37(2): 334-345 (2015) - [j10]Samuel J. Gershman:
A Unifying Probabilistic View of Associative Learning. PLoS Comput. Biol. 11(11) (2015) - [j9]Samuel J. Gershman, Yael Niv:
Novelty and Inductive Generalization in Human Reinforcement Learning. Top. Cogn. Sci. 7(3): 391-415 (2015) - [c12]Samuel Gershman, Joshua B. Tenenbaum:
Phrase similarity in humans and machines. CogSci 2015 - [c11]Eric Schulz, Joshua B. Tenenbaum, David N. Reshef, Maarten Speekenbrink, Samuel Gershman:
Assessing the Perceived Predictability of Functions. CogSci 2015 - 2014
- [j8]Samuel Gershman:
Dopamine Ramps Are a Consequence of Reward Prediction Errors. Neural Comput. 26(3): 467-471 (2014) - [j7]Samuel Gershman, David M. Blei, Kenneth A. Norman, Per B. Sederberg:
Decomposing spatiotemporal brain patterns into topographic latent sources. NeuroImage 98: 91-102 (2014) - [j6]Samuel Gershman, Angela Radulescu, Kenneth A. Norman, Yael Niv:
Statistical Computations Underlying the Dynamics of Memory Updating. PLoS Comput. Biol. 10(11) (2014) - [c10]Samuel Gershman, Noah D. Goodman:
Amortized Inference in Probabilistic Reasoning. CogSci 2014 - [c9]Pedro Tsividis, Samuel Gershman, Joshua B. Tenenbaum, Laura Schulz:
Information Selection in Noisy Environments with Large Action Spaces. CogSci 2014 - [c8]Kimberly L. Stachenfeld, Matthew M. Botvinick, Samuel Gershman:
Design Principles of the Hippocampal Cognitive Map. NIPS 2014: 2528-2536 - [r2]Samuel J. Gershman:
Behavioural Analysis, Bayesian. Encyclopedia of Computational Neuroscience 2014 - [r1]Samuel J. Gershman:
Computation with Dopaminergic Modulation. Encyclopedia of Computational Neuroscience 2014 - [i2]Tejas D. Kulkarni, Ardavan Saeedi, Samuel Gershman:
Variational Particle Approximations. CoRR abs/1402.5715 (2014) - 2013
- [j5]Samuel Gershman, Ahmed A. Moustafa, Elliot A. Ludvig:
Time representation in reinforcement learning models of the basal ganglia. Frontiers Comput. Neurosci. 7: 194 (2013) - [j4]Anastasia Christakou, Samuel Gershman, Yael Niv, Andrew Simmons, Mick Brammer, Katya Rubia:
Neural and Psychological Maturation of Decision-making in Adolescence and Young Adulthood. J. Cogn. Neurosci. 25(11): 1807-1823 (2013) - [c7]Samuel Gershman, Frank Jäkel, Joshua B. Tenenbaum:
Bayesian vector analysis and the perception of hierarchical motion. CogSci 2013 - [c6]Samuel Gershman, Joshua B. Tenenbaum, Alexandre Pouget, Matthew M. Botvinick, Peter Dayan:
Structured cognitive representations and complex inference in neural systems. CogSci 2013 - 2012
- [j3]Samuel Gershman, Edward Vul, Joshua B. Tenenbaum:
Multistability and Perceptual Inference. Neural Comput. 24(1): 1-24 (2012) - [j2]Samuel Gershman, Christopher D. Moore, Michael T. Todd, Kenneth A. Norman, Per B. Sederberg:
The Successor Representation and Temporal Context. Neural Comput. 24(6): 1553-1568 (2012) - [c5]Samuel Gershman, Matthew D. Hoffman, David M. Blei:
Nonparametric variational inference. ICML 2012 - [i1]Samuel Gershman, Matthew D. Hoffman, David M. Blei:
Nonparametric variational inference. CoRR abs/1206.4665 (2012) - 2011
- [j1]Samuel Gershman, David M. Blei, Francisco Pereira, Kenneth A. Norman:
A topographic latent source model for fMRI data. NeuroImage 57(1): 89-100 (2011) - [c4]A. Ross Otto, W. Bradley Knox, Bradley C. Love, Samuel Gershman, Yael Niv, Darrell A. Worthy, W. Todd Maddox, Jared M. Hotaling, Jerome R. Busemeyer, Richard M. Shiffrin:
Computational, Neuroscientific, and Lifespan Perspectives on the Exploration-Exploitation Dilemma. CogSci 2011 - 2010
- [c3]Samuel Gershman, Robert Wilson:
The Neural Costs of Optimal Control. NIPS 2010: 712-720
2000 – 2009
- 2009
- [c2]Samuel Gershman, Ed Vul, Joshua B. Tenenbaum:
Perceptual Multistability as Markov Chain Monte Carlo Inference. NIPS 2009: 611-619 - [c1]Richard Socher, Samuel Gershman, Adler J. Perotte, Per B. Sederberg, David M. Blei, Kenneth A. Norman:
A Bayesian Analysis of Dynamics in Free Recall. NIPS 2009: 1714-1722
Coauthor Index
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