2 papers
stat.ML2026
Beyond identifiability: Learning causal representations with few environments and finite samples
Inbeom Lee, Tongtong Jin, Bryon Aragam
We provide explicit, finite-sample guarantees for learning causal representations from data with a sublinear number of environments. Causal representation learning seeks to provide…
stat.ME2025
G-HIVE: Parameter Estimation and Approximate Inference for Multivariate Response Generalized Linear Models with Hidden Variables
Inbeom Lee, Yang Ning
In practice, there often exist unobserved variables, also termed hidden variables, associated with both the response and covariates. Existing works in the literature mostly focus o…