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2024
Gershman, S. J. What have we learned about artificial intelligence from studying the brain?. Biological Cybernetics 118, 1 - 5 (2024).
2023
Gershman, S. J. & Ullman, T. D. Causal implicatures from correlational statements. PLOS ONE 18, e0286067 (2023).
Tomov, M. S., Tsividis, P. A., Pouncy, T., Tenenbaum, J. B. & Gershman, S. J. The neural architecture of theory-based reinforcement learning. Neuron 111, 1331 - 1344.e8 (2023).
Gershman, S. J. & Cikara, M. Structure learning principles of stereotype change. Psychonomic Bulletin & Review 30, 1273 - 1293 (2023).
2022
Li, Y. et al. An approximate representation of objects underlies physical reasoning. psyArXiv (2022). at <https://psyarxiv.com/vebu5/>
Pouncy, T. & Gershman, S. J. Inductive biases in theory-based reinforcement learning. Cognitive Psychology 138, 101509 (2022).
Gershman, S. J. & Burke, T. Mental control of uncertainty. Cognitive, Affective, & Behavioral Neuroscience 23, 465 - 475 (2022).
Bill, J., Gershman, S. J. & Drugowitsch, J. Visual motion perception as online hierarchical inference. Nature Communications 13, (2022).
2021
Xiang, Y., Graeber, T., Enke, B. & Gershman, S. J. Confidence and central tendency in perceptual judgment. Attention, Perception, & Psychophysics 83, 3024 - 3034 (2021).
McNamee, D., Stachenfeld, K., Botvinick, M. M. & Gershman, S. J. Flexible modulation of sequence generation in the entorhinal-hippocampal system. Nature Neuroscience (2021). doi:10.1038/s41593-021-00831-7
Yang, S., Bill, J., Drugowitsch, J. & Gershman, S. J. Human visual motion perception shows hallmarks of Bayesian structural inference. Scientific Reports 11, (2021).
Dasgupta, I. & Gershman, S. J. Memory as a Computational Resource. Trends in Cognitive Sciences 25, 240 - 251 (2021).
Sosa, F. A., Ullman, T., Tenenbaum, J. B., Gershman, S. J. & Gerstenberg, T. Moral dynamics: Grounding moral judgment in intuitive physics and intuitive psychology. Cognition 217, 104890 (2021).
Tomov, M. S., Schulz, E. & Gershman, S. J. Multi-task reinforcement learning in humans. Nature Human Behaviour (2021). doi:10.1038/s41562-020-01035-y
Pouncy, T., Tsividis, P. & Gershman, S. J. What Is the Model in Model‐Based Planning?. Cognitive Science 45, (2021).
2020
Dasgupta, I., Guo, D., Gershman, S. J. & Goodman, N. D. Analyzing Machine‐Learned Representations: A Natural Language Case Study. Cognitive Science 44, (2020).
Schulz, E., Quiroga, F. & Gershman, S. J. Communicating Compositional Patterns. Open Mind 4, 25 - 39 (2020).
Bill, J., Pailian, H., Gershman, S. J. & Drugowitsch, J. Hierarchical structure is employed by humans during visual motion perception. Proceedings of the National Academy of Sciences 117, 24581 - 24589 (2020).
Sanders, H., Wilson, M. A. & Gershman, S. J. Hippocampal remapping as hidden state inference. eLife 9, (2020).
Gershman, S. J. Origin of perseveration in the trade-off between reward and complexity. Cognition 204, 104394 (2020).
Dasgupta, I., Schulz, E., Tenenbaum, J. B. & Gershman, S. J. A theory of learning to infer. Psychological Review 127, 412 - 441 (2020).
2019
Gershman, S. J. The Generative Adversarial Brain. Frontiers in Artificial Intelligence 2, (2019).
Liu, S., Cushman, F. A., Gershman, S. J., Kool, W. & Spelke, E. S. Hard choices: Children’s understanding of the cost of action selection. . Cognitive Science Society (2019).PDF icon phk_cogsci_2019_final.pdf (276.14 KB)
Sanders, H., Wilson, M. A. & Gershman, S. J. Hippocampal Remapping as Hidden State Inference. (2019). doi:https://doi.org/10.1101/743260PDF icon CBMM-Memo-101.pdf (12.78 MB)
Gershman, S. J. How to never be wrong. Psychonomic Bulletin & Review 26, 13 - 28 (2019).

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