All Publications

2019

K. M. Jozwik, Lee, M., Marques, T., Schrimpf, M., and Bashivan, P., Large-scale hyperparameter search for predicting human brain responses in the Algonauts challenge, in The Algonauts Project: Explaining the Human Visual Brain Workshop 2019 , MIT, Cambridge MA, 2019.
CBMM Funded
CBMM Funded
CBMM Funded
CBMM Memo No.
099
CBMM Funded
A. Adler and Wax, M., Constant modulus algorithms via low-rank approximation, Signal Processing, vol. 160, pp. 263 - 270, 2019.
CBMM Funded
A. Adler, Araya-Polo, M., and Poggio, T., Deep Recurrent Architectures for Seismic Tomography, in 81st EAGE Conference and Exhibition 2019, 2019.
CBMM Funded
CBMM Funded
CBMM Related
CBMM Funded
M. Araya-Polo, Adler, A., Farris, S., and Jennings, J., Fast and Accurate Seismic Tomography via Deep Learning, in Deep Learning: Algorithms and Applications, SPRINGER-VERLAG, 2019.
CBMM Related
W. Xiao, Chen, H., Liao, Q., and Poggio, T., Biologically-Plausible Learning Algorithms Can Scale to Large Datasets, in International Conference on Learning Representations, 2019.
CBMM Funded

2018

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