2026
Doubly Robust Causal Estimation Under Multi-View Network Interference (Student Abstract)
AAAI 2026technical
Estimating causal effects under network interference is challenging especially when edges are heterogeneous and nodes share latent dependencies. We study this realistic setting and propose MVDR, a targeted maximum likelihood (TMLE) framework that learns multi-view representations of covariates and e