Understanding Deep Neural Networks - From Generalization to Interpretability
Institute for Advanced Study via YouTube
Overview
Syllabus
Intro
The Dawn of Deep Learning
Impact of Deep Learning on Mathematical Problems
Numerical Results
Graph Convolutional Neural Networks Graph convolutional neural networks
Two Approaches to Convolution on Graphs
Spectral Graph Convolution
Spectral Filtering using Functional Calculus
Graphs Modeling the Same Phenomenon
Comparing the Repercussion of a Filter on Two Graphs
Transferability of Functional Calculus Filters
Rethinking Transferability
Fundamental Questions concerning Deep Neural Networks
General Problem Setting
What is Relevance?
The Relevance Mapping Problem
Rate-Distortion Viewpoint
Problem Relaxation
Observations
MNIST Experiment
Taught by
Institute for Advanced Study