Recent & Upcoming Talks

Minimally Distorted Interpretable Adversarial Attacks

We provide a new technique to generate highly sparse interpretable adversarial attacks.

Calculus for Data Science

Linear Algebra for Data Science

What is Backpropagation?

We revisit the Backpropagation algorithm, widely used by practitioners to train Deep Neural Networks.

Wavelet-based Low Frequency Adversarial Attacks

We provide new insights into vulnerabilities of deep learning models by showing that training-based and basis-manipulation defense methods are significantly less effective if we restrict the generation of adversarial attacks to the low frequency discrete wavelet transform domain.

Neural Network Approximation Theory

We review classical and modern results in Neural Network Approximation Theory.