Deep Learning

Columbia University - Spring 2020

Class is held in Mudd 1127, Mon and Wed 4:10-5:25pm

Office hours (Monday-Friday)

Monday 3-4pm, CEPSR 620/Video call: Lecturer, Iddo Drori

Tuesday 11-12pm, TA room/Video call: Course Assistant, Chengkuan Chen

Wednesday 2-3pm, TA room/Video call: Course Assistant, Andrew Stirn

Thursday 11-12pm, TA room/Video call: Course Assistant, Shashwat Verma

Friday 10-11am, TA room/Video call: Course Assistant, Dhruv Chamania

First Day of Classes (Tuesday, January 21)

 Lecture 1 (Wednesday, January 22): Introduction

 Lecture 2 (Monday, January 27): Forward and Backpropagation

 Lecture 3 (Wednesday, January 29): Optimization

Competition (Friday, January 31 - Monday, March 16)

 Lecture 4 (Monday, February 3): CNNs

 Lecture 5 (Wednesday, February 5): RNNs

 Lecture 6 (Monday, February 10): Transformers

 Lecture 7 (Wednesday, February 12): GNNs

 Lecture 8 (Monday, February 17): GANs

 Lecture 9 (Wednesday, February 19): VAEs

Lecture 10 (Monday, February 24): Reinforcement Learning

Lecture 11 (Wednesday, February 26): Reinforcement Learning

Lecture 12 (Monday, March 2): Deep Reinforcement Learning

Lecture 13 (Wednesday, March 4): Deep Reinforcement Learning

No classes (Monday, March 9)

Lecture 14 (Wednesday, March 11): Deep Learning in Games

Spring Recess (Monday-Friday, March 16-20)

No classes (Monday, March 23)

No classes (Wednesday, March 25)

Lecture 15 (Monday, March 30): Deep Learning for AutoML

Lecture 16 (Wednesday, April 1): Deep Learning for Autonomous Driving

Lecture 17 (Monday, April 6): Fairness and Privacy for Deep Learning

Lecture 18 (Wednesday, April 8): Deep Learning for Protein Structure Prediction

Lecture 19 (Monday, April 13): Deep Learning for PSP and Medical Imaging

Lecture 20 (Wednesday, April 15): Information Theory for Deep Learning

Lecture 21 (Monday, April 20): Deep Learning and Quantum Computation

Lecture 22 (Wednesday, April 22): Deep Learning and Quantum Computation, TensorFlow Quantum

Lecture 23 (Monday, April 27): Semi-Supervised Deep Learning

Lecture 24 (Wednesday, April 29): Brain Graphs, Deep Graph Library

Lecture 25 (Monday, May 4): Project Presentations
Session 1: Deep Reinforcement Learning
Session 2: Combinatorial Optimization
Session 3: Semi-Supervised Learning
Session 4: Data Dependent Priors
Session 5: GANs
Session 6: Applications: Bioinformatics, NLP, Cyber, Graphics
Session 7: Spatial-Temporal GNNs

Last Day of Classes (Monday, May 4)