All Publications

2019

M. A. P. Idiart, Villavicencio, A., Katz, B., Rennó-Costa, C., and Lisman, J., “How Does the Brain Represents Language and Answers Questions? Using an AI System to Understand the Underlying Neurobiological Mechanisms”, Frontiers in Computational Neuroscience, vol. 13, 2019.
CBMM Funded
A. Adler and Wax, M., “Constant modulus algorithms via low-rank approximation”, Signal Processing, vol. 160, pp. 263 - 270, 2019.
CBMM Funded
S. Ullman, “Using neuroscience to develop artificial intelligence”, Science, vol. 363, no. 6428, pp. 692 - 693, 2019.
CBMM Related
N. Fazeli, Oller, M., Wu, J., Wu, Z., Tenenbaum, J. B., and Rodriguez, A., “See, feel, act: Hierarchical learning for complex manipulation skills with multisensory fusion”, Science Robotics, vol. 4, no. 26, p. eaav3123, 2019.
CBMM Funded
S. Srivastava, Ben-Yosef, G., and Boix, X., “Minimal images in deep neural networks: Fragile Object Recognition in Natural Images”, in International Conference on Learning Representations (ICLR), New Orleans, La, 2019.
CBMM Funded

2018

S. Hu, Ciliberti, D., Grosmark, A. D., Michon, édéric, Ji, D., Penagos, H., áki, örgy, Wilson, M. A., Kloosterman, F., and Chen, Z., “Real-Time Readout of Large-Scale Unsorted Neural Ensemble Place Codes”, Cell Reports, vol. 25, no. 10, pp. 2635 - 2642.e5, 2018.
CBMM Funded
P. Misra, Marconi, A., Peterson, M., and Kreiman, G., “Minimal memory for details in real life events”, Scientific Reports, vol. 8, no. 1, 2018.
CBMM Funded
T. D. Ullman, Stuhlmüller, A., Goodman, N. D., and Tenenbaum, J. B., “Learning physical parameters from dynamic scenes.”, Cognitive Psychology, vol. 104, pp. 57-82, 2018.PDF icon T-Ullman-etal_CogPsych_LearningPhysicalParametersFromDynamicScenes.pdf (3.15 MB)
CBMM Funded
CBMM Memo No.
097
B. Myanganbayar, Mata, C., Dekel, G., Katz, B., Ben-Yosef, G., and Barbu, A., “Partially Occluded Hands: A challenging new dataset for single-image hand pose estimation”. 2018.PDF icon CBMM-Memo-097.pdf (8.53 MB)
CBMM Funded
R. Madhavan, Bansal, A. K., Madsen, J. R., Golby, A. J., Tierney, T. S., Eskandar, E. N., Anderson, W. S., and Kreiman, G., “Neural Interactions Underlying Visuomotor Associations in the Human Brain”, Cerebral Cortex, vol. 1–17, 2018.
CBMM Funded
B. Myanganbayar, Mata, C., Dekel, G., Katz, B., Ben-Yosef, G., and Barbu, A., “Partially Occluded Hands: A challenging new dataset for single-image hand pose estimation”, in The 14th Asian Conference on Computer Vision (ACCV 2018), 2018.PDF icon partially-occluded-hands-6.pdf (8.29 MB)
CBMM Funded
A. Tacchetti, Voinea, S., and Evangelopoulos, G., “Trading robust representations for sample complexity through self-supervised visual experience”, in Advances in Neural Information Processing Systems 31, Montreal, Canada, 2018, pp. 9640–9650.PDF icon trading-robust-representations-for-sample-complexity-through-self-supervised-visual-experience.pdf (3.32 MB)PDF icon NeurIPS2018_Poster.pdf (6.12 MB)
CBMM Memo No.
094
G. Ben-Yosef, Kreiman, G., and Ullman, S., “Spatiotemporal interpretation features in the recognition of dynamic images”. 2018.PDF icon CBMM-Memo-094.pdf (1.21 MB)Package icon CBMM-Memo-094-dynamic-figures.zip (1.8 MB)File fig1.ppsx (147.67 KB)File fig2.ppsx (419.72 KB)File fig4.ppsx (673.41 KB)File figS1.ppsx (587.88 KB)File figS2.ppsx (281.56 KB)
CBMM Funded
CBMM Memo No.
093
L. Arend, Han, Y., Schrimpf, M., Bashivan, P., Kar, K., Poggio, T., DiCarlo, J. J., and Boix, X., “Single units in a deep neural network functionally correspond with neurons in the brain: preliminary results”. 2018.PDF icon CBMM-Memo-093.pdf (2.99 MB)
CBMM Funded
M. S. Livingstone, Arcaro, M. J., and Schade, P. F., “Cortex Is Cortex: Ubiquitous Principles Drive Face-Domain Development”, Trends in Cognitive Sciences, 2018.PDF icon 1-s2.0-S1364661318302572-main.pdf (260.4 KB)
CBMM Related
N. O'Brien, Latessa, S., Evangelopoulos, G., and Boix, X., “The Language of Fake News: Opening the Black-Box of Deep Learning Based Detectors”, in workshop on "AI for Social Good", NIPS 2018, Montreal, Canada, 2018.PDF icon fake-news-paper-NIPS.pdf (147.36 KB)PDF icon fake-news-paper-NIPS_2018_v2.pdf (147.36 KB)
CBMM Funded
L. Isik, Singer, J., Kanwisher, N., ,, WS, A., and Kreiman, G., “What is changing when: decoding visual information in movies from human intracranial recordings”, NeuroImage, vol. 180, Part A, pp. 147-159, 2018.PDF icon Human neurophysiological responses during movies (2.78 MB)
CBMM Funded
Y. - L. Kuo, Barbu, A., and Katz, B., “Deep sequential models for sampling-based planning”, in The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018), Madrid, Spain, 2018.PDF icon kuo2018planning.pdf (637.67 KB)
CBMM Funded
E. Meyers, “Dynamic population coding and its relationship to working memory”, Journal of Neurophysiology, vol. 120, no. 5, pp. 2260 - 2268, 2018.
CBMM Funded
C. Ross, Barbu, A., Berzak, Y., Myanganbayar, B., and Katz, B., “Grounding language acquisition by training semantic parsersusing captioned videos”, in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP 2018), , Brussels, Belgium, 2018.PDF icon Ross-et-al_ACL2018_Grounding language acquisition by training semantic parsing using caption videos.pdf (3.5 MB)
CBMM Funded
A. Tacchetti, Isik, L., and Poggio, T., “Invariant Recognition Shapes Neural Representations of Visual Input”, Annual Review of Vision Science, vol. 4, no. 1, pp. 403 - 422, 2018.PDF icon annurev-vision-091517-034103.pdf (1.55 MB)
CBMM Funded
E. Zisselman, Adler, A., and Elad, M., “Compressed Learning for Image Classification: A Deep Neural Network Approach”, in Handbook of Numerical Analysis, vol. 19, Elsevier, 2018, pp. 3 - 17.
CBMM Related
M. Zhang, Feng, J., Ma, K. Teck, Lim, J. Hwee, Zhao, Q., and Kreiman, G., “Finding any Waldo with zero-shot invariant and efficient visual search”, Nature Communications, vol. 9, 2018.
CBMM Funded
A. C. Spokes and Spelke, E. S., “At 4.5 but not 5.5 years, children favor kin when the stakes are moderately high”, PLOS ONE, vol. 13, no. 8, 2018.
CBMM Related
H. Tang, Schrimpf, M., Lotter, W., Moerman, C., Paredes, A., Caro, J. Ortega, Hardesty, W., Cox, D., and Kreiman, G., “Recurrent computations for visual pattern completion”, Proceedings of the National Academy of Sciences, 2018.PDF icon 1719397115.full_.pdf (1.1 MB)
CBMM Funded

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