Publication

Found 51 results
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2025
Dubach, R., Abdallah, M. S. & Poggio, T. Multiplicative Regularization Generalizes Better Than Additive Regularization. (2025).PDF icon CBMM Memo 158.pdf (4.8 MB)
2023
Tuckute, G., Feather, J., Boebinger, D. & McDermott, J. H. Many but not all deep neural network audio models capture brain responses and exhibit correspondence between model stages and brain regions. PLOS Biology 21, e3002366 (2023).
Aghajan, Z. M., Kreiman, G. & Fried, I. Minute-scale periodicity of neuronal firing in the human entorhinal cortex. Cell Reports 42, 113271 (2023).PDF icon 1-s2.0-S2211124723012834-main.pdf (5.33 MB)
Feather, J., Leclerc, G., Mądry, A. & McDermott, J. H. Model metamers reveal divergent invariances between biological and artificial neural networks. Nature Neuroscience (2023). doi:10.1038/s41593-023-01442-0
Schiatti, L. et al. Modeling Visual Impairments with Artificial Neural Networks: a Review. International Conference on Computer Vision 2023 (2023). at <https://openaccess.thecvf.com/content/ICCV2023W/ACVR/html/Schiatti_Modeling_Visual_Impairments_with_Artificial_Neural_Networks_a_Review_ICCVW_2023_paper.html>
2022
Gershman, S. J. & Burke, T. Mental control of uncertainty. Cognitive, Affective, & Behavioral Neuroscience 23, 465 - 475 (2022).
Zhou, L., Smith, K., Tenenbaum, J. B. & Gerstenberg, T. Mental Jenga: A counterfactual simulation model of causal judgments about physical support. PsyArXiv (2022). at <https://psyarxiv.com/4a5uh>
2021
Ross, C., Barbu, A. & Katz, B. Measuring Social Biases in Grounded Vision and Language Embeddings. (2021).PDF icon CBMM-Memo-126.pdf (1.32 MB)
Ross, C., Katz, B. & Barbu, A. Measuring Social Biases in Grounded Vision and Language Embeddings. NAACL (Annual Conference of the North American Chapter of the Association for Computational Linguistics) (2021).
Dasgupta, I. & Gershman, S. J. Memory as a Computational Resource. Trends in Cognitive Sciences 25, 240 - 251 (2021).
Wang, J., Tao, A., Anderson, W. S., Madsen, J. R. & Kreiman, G. Mesoscopic physiological interactions in the human brain reveal small-world properties. Cell Reports 36, 109585 (2021).
Allen, K. et al. Meta-strategy learning in physical problem solving: the effect of embodied experience. bioRxiv (2021).PDF icon 2021.07.08.451333v2.full_.pdf (3.05 MB)
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).
Yaari, A. Uri et al. Multi-resolution modeling of a discrete stochastic process identifies causes of cancer. International Conference on Learning Representations (2021). at <https://openreview.net/forum?id=KtH8W3S_RE>
Marques, T., Schrimpf, M. & DiCarlo, J. J. Multi-scale hierarchical neural network models that bridge from single neurons in the primate primary visual cortex to object recognition behavior. bioRxiv (2021).PDF icon 2021.03.01.433495v2.full_.pdf (3.23 MB)
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
2020
Ben-Yosef, G., Kreiman, G. & Ullman, S. Minimal videos: Trade-off between spatial and temporal information in human and machine vision. Cognition (2020). doi:10.1016/j.cognition.2020.104263
2019
Marques, T. & DiCarlo, J. J. A meta-analysis of ANNs as models of primate V1 . Bernstein (2019).
Feather, J., Durango, A., Gonzalez, R. & McDermott, J. H. Metamers of neural networks reveal divergence from human perceptual systems. NIPS 2019 (2019). at <https://papers.nips.cc/paper/9198-metamers-of-neural-networks-reveal-divergence-from-human-perceptual-systems>PDF icon Feather_etal_2019_NeurIPS_metamers.pdf (4.7 MB)
Srivastava, S., Ben-Yosef, G. & Boix, X. Minimal images in deep neural networks: Fragile Object Recognition in Natural Images. International Conference on Learning Representations (ICLR) (2019). at <https://arxiv.org/pdf/1902.03227.pdf>
Ullman, S., Dorfman, N. & Harari, D. A model for discovering ‘containment’ relations. Cognition 183, 67 - 81 (2019).
Smith, K. A. et al. Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019) (2019). at <http: //physadept.csail.mit.edu/>PDF icon ADEPT_NeurIPS.pdf (11.07 MB)
2018
Isik, L. & Tacchetti, A. MEG action recognition data. (2018). doi:https://doi.org/10.7910/DVN/KFYY2M
Kool, W. & Botvinick, M. Mental labour. Nature Human Behaviour 2, 899 - 908 (2018).
Misra, P., Marconi, A., Peterson, M. F. & Kreiman, G. Minimal memory for details in real life events. Scientific Reports 8, (2018).

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