Andrzej Banburski

Current Advisees

Simon Alford - UROP
Christian Altamirano - UROP
Anshula Gandhi - Research Assistant
Anna Kooperberg - UROP
Nishka Pant - High School Researcher

Past Advisees

Christian Omar Altamirano Modesto - UROP
Hairuo Guo - Graduate Student
Laura J. Koemmpel - UROP
Diego Alonso Roque Montoya - UROP
Kevin Shen - UROP
Jessica Shi - UROP

CBMM Publications

A. Gupte, Banburski, A., and Poggio, T., “PCA as a defense against some adversaries”. 2022.
A. Banburski and Rangamani, A., “Neural Collapse in Deep Homogeneous Classifiers and the role of Weight Decay”, in IEEE International Conference on Acoustics, Speech and Signal Processing, Singapore, 2022.
M. Xu, Rangamani, A., Banburski, A., Liao, Q., Galanti, T., and Poggio, T., “Dynamics and Neural Collapse in Deep Classifiers trained with the Square Loss”. 2021.
A. Banburski, De La Torre, F., Pant, N., Shastri, I., and Poggio, T., “Distribution of Classification Margins: Are All Data Equal?”. 2021.
J. Gant, Banburski, A., Deza, A., and Poggio, T., “Evaluating the Adversarial Robustness of a Foveated Texture Transform Module in a CNN”, NeurIPS 2021. 2021.
T. Poggio, Liao, Q., and Banburski, A., “Complexity Control by Gradient Descent in Deep Networks”, Nature Communications, vol. 11, 2020.
A. Deza, Liao, Q., Banburski, A., and Poggio, T., “Hierarchically Local Tasks and Deep Convolutional Networks”. 2020.
M. Vuyyuru Reddy, Banburski, A., Pant, N., and Poggio, T., “Biologically Inspired Mechanisms for Adversarial Robustness”. 2020.
T. Poggio and Banburski, A., “An Overview of Some Issues in the Theory of Deep Networks”, IEEJ Transactions on Electrical and Electronic Engineering, vol. 15, no. 11, pp. 1560 - 1571, 2020.
A. Banburski, Gandhi, A., Alford, S., Dandekar, S., Chin, P., and Poggio, T., “Dreaming with ARC”, Learning Meets Combinatorial Algorithms workshop at NeurIPS 2020. 2020.
T. Poggio, Banburski, A., and Liao, Q., “Theoretical issues in deep networks”, Proceedings of the National Academy of Sciences, p. 201907369, 2020.
A. Banburski, Liao, Q., Miranda, B., Rosasco, L., Hidary, J., and Poggio, T., “Dynamics & Generalization in Deep Networks -Minimizing the Norm”, in NAS Sackler Colloquium on Science of Deep Learning, Washington D.C., 2019.
A. Banburski, Liao, Q., Miranda, B., Rosasco, L., Hidary, J., and Poggio, T., “Weight and Batch Normalization implement Classical Generalization Bounds ”, in ICML, Long Beach/California, 2019.
T. Poggio, Banburski, A., and Liao, Q., “Theoretical Issues in Deep Networks”. 2019.
Q. Liao, Banburski, A., and Poggio, T., “Theories of Deep Learning: Approximation, Optimization and Generalization ”, TECHCON 2019. 2019.
T. Poggio, Kur, G., and Banburski, A., “Double descent in the condition number”. 2019.
A. Banburski, Liao, Q., Miranda, B., Poggio, T., Rosasco, L., Hidary, J., and De La Torre, F., “Theory III: Dynamics and Generalization in Deep Networks”. 2018.