Weekly Schedule

Recommended paper list for paper presentations and reviews: click here

Paper presentation slides: click here

Lecture slides will be uploaded on Canvas in the "Modules" section.

1. Week 1 (1/10/2024): Introduction and Course Overview

2. Week 1 (1/12/2024): Deep Learning & Deep Reinforcement Learning (Concise Review)

3. Week 2 (1/17/2024): Out-of-Distribution (OOD) Generalization (Part I)

4. Week 2 (1/19/2024): Out-of-Distribution (OOD) Generalization (Part II)

5. Week 3 (1/24/2024): Out-of-Distribution (OOD) Generalization (Part III)

6. Week 3 (1/26/2024): Adversarial Attack and Defense

7. Week 4 (1/31/2024): Explainability & Interpretability (Part I)

8. Week 4 (2/2/2024): Explainability & Interpretability (Part II)

9. Week 5 (2/7/2024): Uncertainty Estimation/Quantification (Part I)

10. Week 5 (2/9/2024): Uncertainty Estimation/Quantification (Part II)

11. Week 6 (2/14/2024): Uncertainty Estimation/Quantification (Part III)

12. Week 6 (2/16/2024): Uncertainty Estimation/Quantification (Part IV) + Midterm Exam

13. Week 7 (2/21/2024): Safe Reinforcement Learning (Part I)

14. Week 7 (2/23/2024): Safe Reinforcement Learning (Part II)

15. Week 8 (2/28/2024): Safe Reinforcement Learning (Part III)

16. Week 8 (3/1/2024): Language Models, World Models, and Agent Models (Part I)

17. Week 9 (3/6/2024): Language Models, World Models, and Agent Models (Part II)

18. Week 9 (3/8/2024): Language Models, World Models, and Agent Models (Part III)

19. Week 10 (3/13/2024): Final Project Presentations

20. Week 10 (3/15/2024): Final Project Presentations