Course Schedule and Catalog
Course Schedule - Spring Semester 2027
Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).Additional information available here.
Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).Additional information available here.
STAT 645 001 (CRN: 26660)
MODERN PROBABILISTIC ML
Long Title: MODERN PROBABILISTIC MACHINE LEARNING
Department: Statistics
Instructor: Li, Meng
Meeting: 1:00PM - 1:50PM MWF (11-JAN-2027 - 23-APR-2027)
Part of Term: Full Term
Grade Mode: Standard Letter
Course Type: Lecture
Language of Instruction: Taught in English
Method of Instruction: Face to Face
Credit Hours: 3
Course Syllabus:
Course Materials: Rice Campus Store
Restrictions:
Must be enrolled in one of the following Level(s):
Graduate
Section Max Enrollment: 50
Section Enrolled: 0
Total Cross-list Max Enrollment: 100
Total Cross-list Enrolled: 0
Waitlisted: 0 (Max 198)
Current members of the waitlist have priority for available seats.
Enrollment data as of: 2-NOV-2026 6:18AM
Final Exam: No Final Exam
Description: An introduction to modern machine learning through probabilistic modeling and Bayesian decision-making. Topics include Bayesian model construction, posterior prediction, Markov chain Monte Carlo, variational and amortized inference, Gaussian processes, deep learning, generative models, transformers, and foundation models. Particular emphasis is placed on prior-data-fitted networks and related foundation-model approaches for structured and tabular data, uncertainty quantification, calibration, and interpretable discovery. Students complete reproducible computational assignments and a final project. Cross-list: STAT 445.