Talks
Slides of some (recent) talks I've had the pleasure to present
Yes, my network works! But.. what did it learn? @ Mathematics of Deep Learning, BIRS Casa Matemática Oaxaca, 2024
Imaging, Data and Learning: Challenges in biomedical data science @ Hariri Institute at Boston University, 2024
Estimating and controlling for fairness via sensitive attribute predictors @ MSRI (Berkeley), 2023
Overparameterized and Adversarially Robust Sparse Models @ JHU CS seminar, 2020
Slides of some talks I've had the pleasure to present
November 2023: Understanding Deep Nets: Sparse Local Lipschitz functions and Learned Proximal Networks, at SILO (UW-Madison) and TTIC (Chicago)
November 2023: Modern Challenges in Biomedical Imaging, at annual symposium of IBBS, Hopkins.
September 2023: Controlling for fairness with proxy sensitive attributes, at workshop on Algorithms, Fairness and Equity at SLMath Institute @ Berkeley.
September 2022: Overparametrized and Robust Sparse Models, at ICCHA 2022.
August 2022: Responsible ML: Interpretable and fair machine learning models, at sinc(i), Argentina.
December 2018: Invited talk at the workshop Integration of Deep Learning Theories, at NeurIPS'18.
November 2018: Convolutional Networks as Sparse Enforcing Algorithms - an invited lecture at Rene Vidal's course on Mathematics of Deep Learning (JHU).
December 2017: From Shallow to Deep Sparsity with Convolutional Networks - talk at the 2017 CoSIP Intense Course on Deep Learning (TU Berlin).