Presentations

Introduction

Stochastic Gradient Descent

Optimization dynamics, loss landscapes, sharp vs flat minima, double descent, and grokking.

Adversarial Examples

How tiny, imperceptible perturbations fool neural networks, and the Fast Gradient Sign Method (FGSM).