Weekly Schedule

Paper list for paper presentations and summaries: To be updated

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

Week 1 (1/8/2025): Introduction and Course Overview

Week 1 (1/10/2025): Deep Learning & Deep Reinforcement Learning 

Week 2 (1/15/2025): Foundation Models for Robotics 

Week 2 (1/17/2025): Robot Navigation and Scene Understanding

Week 3 (1/22/2025): Out-of-Distribution (OOD) Generalization (Part I)

Week 3 (1/24/2025): Out-of-Distribution (OOD) Generalization (Part II)

Week 4 (1/29/2025): Out-of-Distribution (OOD) Generalization (Part III)

Week 4 (1/31/2025): Domain Generalization & Adversarial Robustness

Week 5 (2/5/2025): Explainability & Interpretability (Part I)

Week 5 (2/7/2025): Explainability & Interpretability (Part II)

Week 6 (2/12/2025): Explainability & Interpretability (Part III)

Week 6 (2/14/2025): Uncertainty Estimation/Quantification (Part I)

Week 7 (2/19/2025): Uncertainty Estimation/Quantification (Part II)

Week 7 (2/21/2025): Uncertainty Estimation/Quantification (Part III)

Week 8 (2/26/2025): Safe Reinforcement Learning (Part I) + Midterm Exam

Week 8 (2/28/2025): Safe Reinforcement Learning (Part II) 

Week 9 (3/5/2025): Safe Reinforcement Learning (Part III) 

Week 9 (3/7/2025): Advanced Topics in Robot Learning

Week 10 (3/12/2025): Final Project Presentations

Week 10 (3/14/2025): Final Project Presentations