All Publications

Submitted

L. Jing, Shen, Y., Dubček, T., Peurifoi, J., Skirlo, S., LeCun, Y., Tegmark, M., and Soljačić, M., “Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNN”. Submitted.PDF icon 1612.05231.pdf (2.3 MB)
CBMM Related
H. Lin and Tegmark, M., “Critical Behavior from Deep Dynamics: A Hidden Dimension in Natural Language”, Submitted.PDF icon Critical Behavior from Deep Dynamics: A Hidden Dimension in Natural Language (1.64 MB)
CBMM Related

2018

A. Ratan N. Murty and Arun, S. P., “Multiplicative mixing of object identity and image attributes in single inferior temporal neurons”, Proceedings of the National Academy of Sciences, vol. 115111736629, no. 14, pp. E3276 - E3285, 2018.
CBMM Related
CBMM Memo No.
077
A. Adler and Wax, M., “Constant Modulus Algorithms via Low-Rank Approximation”. 2018.PDF icon CBMM-Memo-077.pdf (795.61 KB)
CBMM Funded
D. Harari, Tenenabum, J. B., and Ullman, S., “Discovery and usage of joint attention in images”, arXiv.org, 2018.PDF icon 1804.04604v1.pdf (488.85 KB)
CBMM Funded
CBMM Memo No.
076
H. Mhaskar and Poggio, T., “An analysis of training and generalization errors in shallow and deep networks”. 2018.PDF icon CBMM-Memo-076.pdf (772.61 KB)
CBMM Funded
G. Ben-Yosef, Assif, L., and Ullman, S., “Full interpretation of minimal images.”, Cognition, vol. 171, pp. 65-84, 2018.PDF icon Full interpretation of minimal images.pdf (4.55 MB)
CBMM Funded
M. Araya-Polo, Jennings, J., Adler, A., and Dahlke, T., “Deep-learning tomography”, The Leading Edge, vol. 37, no. 1, pp. 58 - 66, 2018.PDF icon TLE2018.pdf (1.9 MB)
CBMM Funded
D. Muir, Fang, X., and Meyers, E., “Brain-Observatory-Toolbox”. 2018.
CBMM Funded
N. Dehghani and Wimmer, R., “A computational perspective of the role of Thalamus in cognition”, arxiv, 2018.PDF icon ThalamusComputationArxiv.pdf (5.12 MB)
CBMM Related

2017

J. A. Leonard, Lee, Y., and Schulz, L. E., “Infants make more attempts to achieve a goal when they see adults persist”, Science, vol. 357, no. 6357, pp. 1290 - 1294, 2017.
CBMM Funded
A. Ratan N. Murty and Arun, S. P., “Effect of silhouetting and inversion on view invariance in the monkey inferotemporal cortex”, Journal of Neurophysiology, vol. 11823, no. 1, pp. 353 - 362, 2017.
CBMM Related
N. Grossman, Bono, D., Dedic, N., Kodandaramaiah, S. B., Rudenko, ii, A., Suk, H. - J., Cassara, A. M., Neufeld, E., Kuster, N., Tsai, L. - H., Pascual-Leone, A., and Boyden, E. S., “Noninvasive Deep Brain Stimulation via Temporally Interfering Electric Fields”, Cell, vol. 169, no. 6, pp. 1029 - 1041.e16, 2017.
CBMM Funded
A. Ratan N. Murty and Arun, S. P., “A Balanced Comparison of Object Invariances in Monkey IT Neurons”, eneuro, vol. 4, no. 2, pp. ENEURO.0333-16.2017, 2017.
CBMM Related
A. Ratan N. Murty and Arun, S. P., “Seeing a straight line on a curved surface: decoupling of patterns from surfaces by single IT neurons”, Journal of Neurophysiology, vol. 11773, no. 1, pp. 104 - 116, 2017.
CBMM Related
W. Kool, Gershman, S. J., and Cushman, F. A., “Cost-Benefit Arbitration Between Multiple Reinforcement-Learning Systems.”, Psychol Sci, vol. 28, no. 9, pp. 1321-1333, 2017.
CBMM Funded
B. M. Lake, Ullman, T. D., Tenenbaum, J. B., and Gershman, S. J., “Building machines that learn and think like people.”, Behav Brain Sci, vol. 40, p. e253, 2017.
CBMM Funded
E. Schulz, Tenenbaum, J. B., Duvenaud, D., Speekenbrink, M., and Gershman, S. J., “Compositional inductive biases in function learning.”, Cogn Psychol, vol. 99, pp. 44-79, 2017.
CBMM Funded
CBMM Memo No.
073
T. Poggio, Liao, Q., Miranda, B., Rosasco, L., Boix, X., Hidary, J., and Mhaskar, H., “Theory of Deep Learning III: explaining the non-overfitting puzzle”. 2017.PDF icon CBMM-Memo-073.pdf (2.65 MB)PDF icon CBMM Memo 073 v2 (revised 1/15/2018) (2.81 MB)PDF icon CBMM Memo 073 v3 (revised 1/30/2018) (2.72 MB)
CBMM Funded
CBMM Memo No.
072
C. Zhang, Liao, Q., Rakhlin, A., Miranda, B., Golowich, N., and Poggio, T. A., “Theory of Deep Learning IIb: Optimization Properties of SGD”. 2017.PDF icon CBMM-Memo-072.pdf (3.66 MB)
CBMM Funded
CBMM Memo No.
071
F. Cano-Córdoba, Sarma, S., and Subirana, B., “Theory of Intelligence with Forgetting: Mathematical Theorems Explaining Human Universal Forgetting using “Forgetting Neural Networks””. 2017.PDF icon CBMM-Memo-071.pdf (2.54 MB)
CBMM Funded
A. Tacchetti, Isik, L., and Poggio, T., “Invariant recognition drives neural representations of action sequences”, PLOS Computational Biology, vol. 13, no. 12, p. e1005859, 2017.PDF icon journal.pcbi_.1005859.pdf (9.24 MB)
CBMM Funded
J. Wu, Lu, E., Kohli, P., Freeman, B., and Tenenbaum, J., “Learning to See Physics via Visual De-animation”, Advances in Neural Information Processing Systems 30. pp. 152–163, 2017.PDF icon Learning to See Physics via Visual De-animation (1.11 MB)
CBMM Funded
J. Wu, Wang, Y., Xue, T., Sun, X., Freeman, B., and Tenenbaum, J., “MarrNet: 3D Shape Reconstruction via 2.5D Sketches”, Advances in Neural Information Processing Systems 30. Curran Associates, Inc., Long Beach, CA, pp. 540–550, 2017.PDF icon MarrNet: 3D Shape Reconstruction via 2.5D Sketches (6.25 MB)
CBMM Funded
zhoutong zhang, Li, Q., Huang, Z., Wu, J., Tenenbaum, J., and Freeman, B., “Shape and Material from Sound”, Advances in Neural Information Processing Systems 30. Long Beach, CA, pp. 1278–1288, 2017.
CBMM Funded