Publication

Export 903 results:
2016
Mlynarski, W. & McDermott, J. H. Learning Mid-Level Codes for Natural Sounds. Advances and Perspectives in Auditory Neuroscience (2016).PDF icon APAN_large_JHM kopia.pdf (19.74 MB)
Mlynarski, W. & McDermott, J. H. Learning mid-level codes for natural sounds. Computational and Systems Neuroscience (Cosyne) 2016 (2016). at <http://www.cosyne.org/c/index.php?title=Cosyne2016_posters_2>PDF icon Wiktor_COSYNE_2015_hierarchy_final.pdf (2.52 MB)
Morales, A., Premtoon, V., Avery, C., Felshin, S. & Katz, B. Learning to Answer Questions from Wikipedia Infoboxes. The 2016 Conference on Empirical Methods on Natural Language Processing (EMNLP 2016) (2016).PDF icon Morales-EMNLP2016.pdf (197.28 KB)
Owens, A., Isola, P., McDermott, J. H., Freeman, W. T. & Torralba, A. Lecture Notes in Computer ScienceComputer Vision – ECCV 2016Ambient Sound Provides Supervision for Visual Learning. 14th European Conference on Computer Vision 801 - 816 (2016). doi:10.1007/978-3-319-46448-010.1007/978-3-319-46448-0_48
Katz, B. & Barbu, A. A look back at the June 2016 BMM Workshop in Sestri Levante, Italy. (2016).PDF icon Sestri Levante Review (359.33 KB)
Mlynarski, W. & McDermott, J. H. Lossy Compression of Sound Texture by the Human Auditory System. Society for Neuroscience Meeting (2016).
Tang, H. et al. A machine learning approach to predict episodic memory formation. 2016 Annual Conference on Information Science and Systems (CISS) 539 - 544 (2016). doi:10.1109/CISS.2016.7460560
Making learning count: A large-scale randomized control trial testing the effects of core mathematical training on school readiness in young children. International Mind, Brain and Education Society (2016).
Winston, P. Henry. Marvin L. Minsky (1927–2016) Scientist and inventor was a visionary founder of AI. (2016).PDF icon Marvin L. Minsky (1927–2016) Scientist and inventor was a visionary founder of AI.pdf (559.42 KB)
Jara-Ettinger, J., Piantadosi, S., Spelke, E. S., Levy, R. & Gibson, E. Mastery of the logic of natural numbers is not the result of mastery of counting: Evidence from late counters. . Developmental Science (2016). doi:10.1111/desc.12459
Harari, D., Gao, T., Kanwisher, N., Tenenbaum, J. B. & Ullman, S. Measuring and modeling the perception of natural and unconstrained gaze in humans and machines. (2016).PDF icon CBMM-Memo-059.pdf (1.71 MB)
Conway, B. R., Lafer-Sousa, R. & Hermann, K. Mechanisms of color perception and cognition covered by# thedress. VSS 2016 16, 746-746 (2016).
Conway, B. R., Lafer-Sousa, R. & Hermann, K. Mechanisms of color perception and cognition covered by #thedress. VSS 2016 16, 746 (2016).
Krafft, P., Baker, C., Pentland, A. & Tenenbaum, J. B. Modeling Human Ad Hoc Coordination. AAAI (2016).PDF icon krafft_aaai2016.pdf (247.58 KB)
Nakahashi, R., Baker, C. & Tenenbaum, J. B. Modeling human understanding of complex intentional action with a Bayesian nonparametric subgoal model. AAAI (2016).PDF icon nakahashi_aaai2016.pdf (1.74 MB)
The naive utility calculus: Computational principles underlying commonsense psychology. (2016).
Jara-Ettinger, J., Gweon, H., Schulz, L. & Tenenbaum, J. B. The naive utility calculus: computational principles underlying social cognition. Trends Cogn Sci. (2016). doi:10.1016/j.tics.2016.05.011
Bramley, N., Gerstenberg, T. & Tenenbaum, J. B. Natural science: Active learning in dynamic physical microworlds. 38th Annual Meeting of the Cognitive Science Society (2016).PDF icon Natural Science (Bramley, Gerstenberg, Tenenbaum, 2016).pdf (5.39 MB)
Morère, O., Veillard, A., Chandrasekhar, V. & Poggio, T. Nested Invariance Pooling and RBM Hashing for Image Instance Retrieval. arXiv.org (2016). at <https://arxiv.org/abs/1603.04595>PDF icon 1603.04595.pdf (2.9 MB)
Kreiman, G. Neural Information Processing Systems (NIPS) 2015 Review. (2016).PDF icon Read the Views & Review article by Gabriel Kreiman (443.87 KB)
Robertson, C. E., Hermann, K., Mynick, A., Kravitz, D. J. & Kanwisher, N. Neural Representations Integrate the Current Field of View with the Remembered 360° Panorama. Current Biology (2016). doi:10.1016/j.cub.2016.07.002
Tan, C. & Poggio, T. Neural Tuning Size in a Model of Primate Visual Processing Accounts for Three Key Markers of Holistic Face Processing. Public Library of Science | PLoS ONE 1(3): e0150980, (2016).PDF icon journal.pone_.0150980.PDF (384.15 KB)
Meyers, E., Dean, M. & Hale, G. J. New Data Science tools for analyzing neural data and computational models. Society for Neuroscience (2016).
Lewis, O. & Poggio, T. From Neuron to Cognition via Computational Neuroscience (The MIT Press, 2016). at <https://mitpress.mit.edu/neuron-cognition>
Kamps, F. S., Julian, J. B., Kubilius, J., Kanwisher, N. & Dilks, D. D. The occipital place area represents the local elements of scenes. NeuroImage 132, 417 - 424 (2016).

Pages