All Publications

2017

CBMM Funded
Y. Han, Roig, G., Geiger, G., and Poggio, T., Is the Human Visual System Invariant to Translation and Scale?, in AAAI Spring Symposium Series, Science of Intelligence, 2017.
CBMM Funded
J. Mutch, Anselmi, F., Tacchetti, A., Rosasco, L., Leibo, J., and Poggio, T., Invariant Recognition Predicts Tuning of Neurons in Sensory Cortex, in Computational and Cognitive Neuroscience of Vision, Springer, 2017, pp. 85-104.
CBMM Funded

2016

W. Lotter, Kreiman, G., and Cox, D., Unsupervised Learning of Visual Structure using Predictive Generative Networks, in International Conference on Learning Representations (ICLR), San Juan, Puerto Rico, 2016.
CBMM Funded
M. Nickel, Murphy, K., Tresp, V., and Gabrilovich, E., A Review of Relational Machine Learning for Knowledge Graphs, Proceedings of the IEEE, vol. 104, no. 1, pp. 11 - 33, 2016.PDF icon 1503.00759v3.pdf (1.53 MB)
CBMM Funded
Q. Liao, Leibo, J. Z., and Poggio, T., How Important Is Weight Symmetry in Backpropagation?, in Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, AZ., 2016.PDF icon liao-leibo-poggio.pdf (191.91 KB)
CBMM Funded
T. Poggio, Deep Leaning: Mathematics and Neuroscience, A Sponsored Supplement to Science, vol. Brain-Inspired intelligent robotics: The intersection of robotics and neuroscience, pp. 9-12, 2016.
CBMM Funded
CBMM Memo No.
056
CBMM Funded
F. Anselmi, Rosasco, L., and Poggio, T., On invariance and selectivity in representation learning, Information and Inference: A Journal of the IMA, p. iaw009, 2016.PDF icon imaiai.iaw009.full_.pdf (267.87 KB)
CBMM Funded
CBMM Funded
W. Mlynarski and McDermott, J. H., Learning mid-level codes for natural sounds, Computational and Systems Neuroscience (Cosyne) 2016. Salt Lake City, UT, 2016.PDF icon Wiktor_COSYNE_2015_hierarchy_final.pdf (2.52 MB)
CBMM Funded