teaching

classes, workshops, and teaching materials

Carnegie Mellon University

Probabilistic Graphical Models
10-708
Spring 2020: Guest Lecturer
  • Lecture 19: Reinforcement Learning as Inference in GM (part 1) slides  video  notes
  • Lecture 20: Reinforcement Learning as Inference in GM (part 2) slides  video  notes
  • Lecture 27: Elements of Meta-Learning slides  video 
Probabilistic Graphical Models
10-708
Spring 2019: Head TA & Co-lecturer
  • Lecture 6: Parameter learning in partially observed BNs slides  video  notes
  • Lecture 20: Sequential decision making (part 1): The framework slides  video  notes
  • Lecture 21: Sequential decision making (part 2): The algorithms slides  video  notes
  • Lecture 23: Bayesian non-parameterics slides  video  notes
  • Lecture 26: Gaussian processes (GPs) and elements of meta-learning slides  video  notes
Probabilistic Graphical Models
10-708
Spring 2017: TA & Guest Lecturer
  • Homeworks and recitations link link 
  • Lecture on Graphical Models and Deep Learning slides  notes
Topics in Deep Learning
10-807
Fall 2016: TA


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