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cs.LG2026
Peer Effects in Signed Networks: Separating Influence Through Positive and Negative Ties
Xiaojing Du, Jiuyong Li, Lin Liu +3
Evaluating network interventions requires understanding how treatment affects people through their social relationships. Counting treated neighbors without distinguishing supportiv…
cs.LG2026
When Interference Graphs Evolve: Doubly Robust Estimation of Dynamic Peer Effects
Xiaojing Du
Peer effects are difficult to estimate when interaction graphs evolve because pre-assignment network history, dynamic peer exposure, and post-assignment network change have distinc…
cs.LG2026
Transportable Causal Effect Estimation across Networks under Interference
Xiaojing Du, Jiuyong Li, Lin Liu +3
Estimating causal effects under network interference typically assumes that the network used for training and the network used for deployment coincide. In practice, an intervention…