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Found 912 results
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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)
Houlihan, S. Dae & Saxe, R. Modeling emotion attributions as inference in an intuitive theory of mind. Mechanisms Underlying Emotion Regulation and Developmental Psychopathology (2017).
Theurel, D. Modeling brain dynamics using mathematics from quantum mechanics. Peter Chin's Lab, Boston University Boston University, (2017).
Winston, P. Henry. Model-based Story Summary. 6th Workshop on Computational Models of Narrative (2015). doi:10.4230/OASIcs.CMN.2015.157
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
Ben-Yosef, G., Yachin, A. & Ullman, S. A model for interpreting social interactions in local image regions. AAAI Spring Symposium Series, Science of Intelligence (2017). at <http://www.aaai.org/ocs/index.php/SSS/SSS17/paper/view/15354>PDF icon 2017-Ben-Yosef_Yachin_Ullman-A_model_for_interpreting_social_interactions_in_local_image_regions.pdf (1.53 MB)
Ben-Yosef, G., Assif, L., Harari, D. & Ullman, S. A model for full local image interpretation. Cognitive Science Society (2015).PDF icon Full object interpretation CogSci 2015 Print version.pdf (707.34 KB)
Ullman, S., Dorfman, N. & Harari, D. A model for discovering ‘containment’ relations. Cognition 183, 67 - 81 (2019).
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)
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
McCoy, J. P. & Ullman, T. D. A Minimal Turing Test. Journal of Experimental Social Psychology 79, 1 - 8 (2018).
Misra, P., Marconi, A., Peterson, M. F. & Kreiman, G. Minimal memory for details in real life events. Scientific Reports 8, (2018).
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, T. D., Spelke, E. S., Battaglia, P. & Tenenbaum, J. B. Mind Games: Game Engines as an Architecture for Intuitive Physics. Trends in Cognitive Science 21, 649 - 665 (2017).PDF icon Preprint submitted to Trends in Cognitive Science (17.64 MB)
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)
Ellis, K. & Lewis, O. Metareasoning in Symbolic Domains. NIPS Workshop | Bounded Optimality and Rational Metareasoning (2015). at <https://sites.google.com/site/boundedoptimalityworkshop/>PDF icon metareasoning_submitted.pdf (491.95 KB)
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)
Marques, T. & DiCarlo, J. J. A meta-analysis of ANNs as models of primate V1 . Bernstein (2019).
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).
Kool, W. & Botvinick, M. Mental labour. Nature Human Behaviour 2, 899 - 908 (2018).
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>
Gershman, S. J. & Burke, T. Mental control of uncertainty. Cognitive, Affective, & Behavioral Neuroscience 23, 465 - 475 (2022).
Dasgupta, I. & Gershman, S. J. Memory as a Computational Resource. Trends in Cognitive Sciences 25, 240 - 251 (2021).
Isik, L. & Tacchetti, A. MEG action recognition data. (2018). doi:https://doi.org/10.7910/DVN/KFYY2M
Conway, B. R., Lafer-Sousa, R. & Hermann, K. Mechanisms of color perception and cognition covered by# thedress. VSS 2016 16, 746-746 (2016).

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