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2017
Isik, L., Tacchetti, A. & Poggio, T. A fast, invariant representation for human action in the visual system. J Neurophysiol jn.00642.2017 (2017). doi:10.1152/jn.00642.2017PDF icon Author's last draft (695.63 KB)
Gerstenberg, T., Zhou, L., Smith, K. A. & Tenenbaum, J. B. Faulty Towers: A counterfactual simulation model of physical support. Proceedings of the 39th Annual Conference of the Cognitive Science Society (2017).PDF icon Faulty Towers A counterfactual simulation model of physical support, Gerstenberg et al., 2017.pdf (8.75 MB)
Liang, T., Poggio, T., Rakhlin, A. & Stokes, J. Fisher-Rao Metric, Geometry, and Complexity of Neural Networks. arXiv.org (2017). at <https://arxiv.org/abs/1711.01530>PDF icon 1711.01530.pdf (966.99 KB)
Spokes, A. C., Venkatesan, T. & Spelke, E. S. Five-month-old infants attend to responsive caregivers. Cognitive Development Society (CDS) (2017). at <https://cogdevsoc.org/wp-content/uploads/2017/10/CDS2017AbstractBook.pdf>
Subirana, B., Bagiati, A. & Sarma, S. On the Forgetting of College Academics: at "Ebbinghaus Speed"?. (2017).PDF icon CBMM Memo 068-On Forgetting - June 18th 2017 v2.pdf (713.7 KB)
Saxe, R. & Houlihan, S. Dae. Formalizing emotion concepts within a Bayesian model of theory of mind. Current Option in Psychology 17, 15-21 (2017).PDF icon 1-s2.0-S2352250X17300283-main.pdf (613.77 KB)
Spokes, A. C. & Spelke, E. S. Four-year-old children favor kin when the stakes are higher. Cognitive Development Society (CDS) (2017). at <https://cogdevsoc.org/wp-content/uploads/2017/10/CDS2017AbstractBook.pdf>
Sliwa, J. & Freiwald, W. A. From agents to actions to interactions: Uncovering multiple social networks in the primate brain. Society for Social and Affective Neuroscience (2017).
Ben-Yosef, G., Assif, L. & Ullman, S. Full interpretation of minimal images. (2017).PDF icon CBMM Memo 061 v.1 (4.64 MB)PDF icon CBMM Memo 061 v.2 (5.41 MB)
Zhang, Z. et al. Generative modeling of audible shapes for object perception. The IEEE International Conference on Computer Vision (ICCV) (2017). at <http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Generative_Modeling_of_ICCV_2017_paper.html>
Tsividis, P., Pouncy, T., Xu, J. L., Tenenbaum, J. B. & Gershman, S. J. Human Learning in Atari. AAAI Spring Symposium Series (2017).PDF icon Tsividis et al - Human Learning in Atari.pdf (844.47 KB)
Han, Y., Roig, G., Geiger, G. & Poggio, T. On the Human Visual System Invariance to Translation and Scale. Vision Sciences Society (2017).
Han, Y., Roig, G., Geiger, G. & Poggio, T. Is the Human Visual System Invariant to Translation and Scale?. AAAI Spring Symposium Series, Science of Intelligence (2017).
Leonard, J. A., Lee, Y. & Schulz, L. Infants make more attempts to achieve a goal when they see adults persist. Science 357, 1290 - 1294 (2017).
Wu, Y. & Schulz, L. Inferring Beliefs and Desires From Emotional Reactions to Anticipated and Observed Events. Child Development (2017). doi:10.1111/cdev.12759PDF icon Wu_et_al-2017-Child_Development.pdf (883.1 KB)
Tacchetti, A., Isik, L. & Poggio, T. Invariant action recognition dataset. (2017). at <https://doi.org/10.7910/DVN/DMT0PG>
Tacchetti, A., Isik, L. & Poggio, T. Invariant recognition drives neural representations of action sequences. PLOS Computational Biology 13, e1005859 (2017).PDF icon journal.pcbi_.1005859.pdf (9.24 MB)
Tacchetti, A., Isik, L. & Poggio, T. Invariant recognition drives neural representations of action sequences. PLoS Comp. Bio (2017).
Mutch, J. et al. Computational and Cognitive Neuroscience of Vision 85-104 (Springer, 2017).
Traer, J. & McDermott, J. H. Investigating audition with a generative model of impact sounds. Annual Meeting of Acoustical Society of America (2017).
Learning a commonsense moral theory. (2017).
Mlynarski, W. & McDermott, J. H. Learning Mid-Level Auditory Codes from Natural Sound Statistics. (2017).PDF icon MlynarskiMcDermott_Memo060.pdf (7.11 MB)
Mlynarski, W. & McDermott, J. H. Learning Mid-Level Codes for Natural Sounds. Association for Otolaryngology Mid-Winter Meeting (2017).
Wu, J., Lu, E., Kohli, P., Freeman, W. T. & Tenenbaum, J. B. Learning to See Physics via Visual De-animation. Advances in Neural Information Processing Systems 30 152–163 (2017). at <http://papers.nips.cc/paper/6620-learning-to-see-physics-via-visual-de-animation.pdf>PDF icon Learning to See Physics via Visual De-animation (1.11 MB)
Traer, J. & McDermott, J. H. A library of real-world reverberation and a toolbox for its analysis and measurement. Annual Meeting of Acoustical Society of America (2017).

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