Spring 2026 Statistics GR8101 section 001

TOPICS IN APPLIED STATISTICS

Applied Causality

Call Number 14159
Day & Time
Location
T 10:10am-12:00pm
331 Uris Hall
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 8 students (25 max) as of 6:06PM Tuesday, January 20, 2026
Subject Statistics
Number GR8101
Section 001
Division Graduate School of Arts and Sciences
Open To GSAS
Note PhD students only
Section key 20261STAT8101G001