Explore advanced concepts in deep learning through this comprehensive lecture by Joan Bruna from NYU, covering topics such as symmetry, transformations, time series analysis, continuous domain applications, geometric stability, convolutional networks, and scattering representations. Delve into the intricacies of reproducing kernels, convolutional kernel networks, and spatial support while gaining insights into various deep learning models and their applications.

Syllabus

Introduction
Motivation
Symmetry
Transformations
Time Series
Continuous Domain
Geometric Stability
Convolutional Network
Other Models
Spatial Support
Convolutional Kernel Networks
Reproducing Kernels
Scattering Representation