Advanced Deep Learning

E9:309 • Fall 2021

Announcements

First class

First class on August 4, 2021 3:00 PM.

Logistics

Instructor

Dr. Sriram Ganapathy

sriramg@iisc.ac.in

Office: C 334 (2nd Floor)

Class Times

Mon & Wed

3:00 PM – 4:30 PM

Microsoft Teams - Meeting Link: Link

Microsoft Teams - Channel: Link

Lab: C 328 (2nd Floor)

First Class: Jan 6, 2025

Teaching Assistants

Varun Krishna

{varunkrishna} aT iisc doT ac doT in

Syllabus

  • Visual and Time Series Modeling - Semantic Models, Recurrent neural models and LSTM models, Encoder-decoder models, Attention models.
  • Representation Learning, Causality And Explainability - t-SNE visualization, Hierarchical Representation, semantic embeddings, gradient and perturbation analysis, Topics in Explainable learning, Structural causal models.
  • Unsupervised Learning: - Restricted Boltzmann Machines, Variational Autoencoders, Generative Adversarial Networks.
  • New Architectures - Capsule networks, End-to-end models, Transformer Networks.
  • Applications - Applications in in NLP, Speech, Image/Video domains in all modules.

Grading Details

60%
3 monthly research projects

From three different domains (Speech/Audio, Text, Images/Videos, Biomedical, Financial, Chemical/Physical Sciences/Mathematical Sciences)

10%
Midterm Exam
30%
Final Exam

Pre-requisites

Linear Algebra
Random Process
Basic Machine Learning/Pattern Recognition course
Good background in Python programming.

References

A significant portion of the material would come from research papers/tutorials in the domain.
Lecture notes in pdf format.
Deep Learning

I. Goodfellow, Y. Bengio, A. Courville, MIT Press, 2016.

HTML Version

Slides

04-08-2021
Introduction. Setting the stage for the course.