All Publications

2018

W. Mlynarski and McDermott, J. H., “Learning Mid-Level Auditory Codes from Natural Sound Statistics”, Neural Computation, vol. 30, no. 3, pp. 631-669, 2018.
CBMM Funded
W. Mlynarski and McDermott, J. H., “Co-occurrence statistics of natural sound features predict perceptual grouping”, Computational and Systems Neuroscience (COSYNE). Denver, Colorado, 2018.
CBMM Funded
J. Traer and McDermott, J. H., “Human inference of force from impact sounds: Perceptual evidence for inverse physics”, Annual Meeting of the Acoustical Society, vol. 143, no. 3. 2018.
CBMM Related
K. Wu, Wu, E., and Kreiman, G., “Learning Scene Gist with Convolutional Neural Networks to Improve Object Recognition”, arXiv | Cornell University, vol. arXiv:1803.01967, 2018.
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)PDF icon CBMM-Memo-076v2.pdf (2.67 MB)
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
B. Katz, Borchardt, G., Felshin, S., and Mora, F., “A Natural Language Interface for Mobile Devices”, in The Wiley Handbook of Human Computer Interaction, First., vol. 2, John Wiley & Sons , 2018, pp. 539-559.
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
G. Ben-Yosef, Assif, L., and Ullman, S., “Full interpretation of minimal images”, Cognition, vol. 171, pp. 65 - 84, 2018.
CBMM Funded
D. Muir, Fang, X., and Meyers, E., “Brain-Observatory-Toolbox”. 2018.
CBMM Funded
A. Adler and Wax, M., “Constant Modulus Beamforming Via Low-Rank Approximation”, in 2018 IEEE Statistical Signal Processing Workshop (SSP), Freiburg im Breisgau, Germany, 2018.
CBMM Related
Fde Avila Belbute-Peres, Smith, K. A., Allen, K., Tenenbaum, J. B., and Kolter, Z., “End-to-end differentiable physics for learning and control”, Advances in Neural Information Processing Systems 31 (NIPS 2018). 2018.PDF icon 7948-end-to-end-differentiable-physics-for-learning-and-control.pdf (794.17 KB)
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
L. Isik, Tacchetti, A., and Poggio, T., “A fast, invariant representation for human action in the visual system”, Journal of Neurophysiology, 2018.
CBMM Funded
L. Isik and Tacchetti, A., “MEG action recognition data”. 2018.
CBMM Funded
O. Lewis, “Structured learning and inference with neural networks and generative models”, 2018.
CBMM Funded
W. Mlynarski and McDermott, J. H., “Co-occurrence statistics of natural sound features predict perceptual grouping”, Computational and Systems Neuroscience (Cosyne) 2018. 2018.
CBMM Funded
T. Poggio and Liao, Q., “Theory I: Deep networks and the curse of dimensionality”, Bulletin of the Polish Academy of Sciences: Technical Sciences, vol. 66, no. 6, 2018.PDF icon 02_761-774_00966_Bpast.No_.66-6_28.12.18_K1.pdf (1.18 MB)
CBMM Funded
T. Poggio and Liao, Q., “Theory II: Deep learning and optimization”, Bulletin of the Polish Academy of Sciences: Technical Sciences, vol. 66, no. 6, 2018.PDF icon 03_775-788_00920_Bpast.No_.66-6_31.12.18_K2.pdf (5.43 MB)
CBMM Funded
M. Schrimpf and Kubilius, J., “Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like?”, bioRxiv preprint, 2018.PDF icon Brain-Score bioRxiv.pdf (789.83 KB)
CBMM Related
J. Sliwa, Marvel, S. R., Ianni, G. A., and Freiwald, W. A., “Comparing human and monkey neural circuits for processing social scenes”, Cognitive Neuroscience Society Annual Meeting (CNS), Boston, MA. 2018.
CBMM Funded
J. Traer and McDermott, J. H., “Human recognition of environmental sounds is not always robust to reverberation”, Annual Meeting of the Acoustical Society, vol. 143, no. 3. 2018.
CBMM Related
J. Wang, Zhang, Z., Xie, C., Zhou, Y., Premachandran, V., Zhu, J., Xie, L., and Yuille, A., “Visual Concepts and Compositional Voting”, Annals of Mathematical Sciences and Applications (AMSA), vol. 3, no. 1, pp. 151–188, 2018.
CBMM Funded

2017

J. A. Leonard, Lee, Y., and Schulz, L., “Infants make more attempts to achieve a goal when they see adults persist”, Science, vol. 357, no. 6357, pp. 1290 - 1294, 2017.
CBMM Funded
M. L. Leavitt, Mendoza-Halliday, D., and J.C., M. - T., “Sustained Activity Encoding Working Memories: Not Fully Distributed”, Trends in Neurosciences , vol. 40 , no. 6, pp. 328-346, 2017.
CBMM Related

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