2 papers
cs.LG2026
Rank Is Not Capacity: Spectral Occupancy for Latent Graph Models
Nikolaos Nakis, Panagiotis Promponas, Konstantinos Tsirkas +4
Graph representation learning has become a standard approach for analyzing networked data, with latent embeddings widely used for link prediction, community detection, and related…
math.ST2025
What Makes Treatment Effects Identifiable? Characterizations and Estimators Beyond Unconfoundedness
Yang Cai, Alkis Kalavasis, Katerina Mamali +2
Most of the widely used estimators of the average treatment effect (ATE) in causal inference rely on the assumptions of unconfoundedness and overlap. Unconfoundedness requires that…