Publication

Found 45 results
Author Title Type [ Year(Asc)]
Filters: Author is Gershman, Samuel J.  [Clear All Filters]
2024
Gershman, S. J. What have we learned about artificial intelligence from studying the brain?. Biological Cybernetics 118, 1 - 5 (2024).
2023
Xiang, Y., Landy, J., Cushman, F. A., Vélez, N. & Gershman, S. J. Actual and counterfactual effort contribute to responsibility attributions in collaborative tasks. Cognition 241, 105609 (2023).
Gershman, S. J. & Ullman, T. D. Causal implicatures from correlational statements. PLOS ONE 18, e0286067 (2023).
Xiang, Y., Vélez, N. & Gershman, S. J. Collaborative decision making is grounded in representations of other people’s competence and effort. Journal of Experimental Psychology: General 152, 1565 - 1579 (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).
Yu, C., Burgess, N., Sahani, M. & Gershman, S. J. Successor-Predecessor Intrinsic Exploration. Advances in Neural Information Processing Systems 36 (NeurIPS 2023) (2023). at <https://proceedings.neurips.cc/paper_files/paper/2023/hash/e6f2b968c4ee8ba260cd7077e39590dd-Abstract-Conference.html>
Vélez, N., Chen, A. M., Burke, T., Cushman, F. A. & Gershman, S. J. Teachers recruit mentalizing regions to represent learners’ beliefs. Proceedings of the National Academy of Sciences 120, (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).

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