| Call Number | 14159 |
|---|---|
| Day & Time Location |
T 10:10am-12:00pm To be announced |
| Points | 3 |
| Grading Mode | Standard |
| Approvals Required | None |
| Instructor | David Blei |
| Type | LECTURE |
| Method of Instruction | In-Person |
| Course Description | .This seminar explores the principle of invariance and its role in causal reasoning. We will study algorithms that connect invariance to causality, how these ideas extend to representation learning, and examine applications across the sciences and social sciences. Some subjects will include invariant causal prediction, causal representation learning, robust learning from multiple environments, and empirical Bayes. |
| Web Site | Vergil |
| Department | Statistics |
| Enrollment | 18 students (25 max) as of 1:05PM Sunday, May 10, 2026 |
| Subject | Statistics |
| Number | GR8101 |
| Section | 001 |
| Division | Graduate School of Arts and Sciences |
| Open To | GSAS |
| Note | PhD students only |
| Section key | 20261STAT8101G001 |