A new interference modeling approach with partial attentions and message amplification captures varying neighbor importance and scale to improve ITE estimation on graphs.
arXiv preprint arXiv:2407.05287 , year=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
PEQ-Net uses policy-aware reparameterization of ICE Q-functions and kernel mean embeddings in a shared encoder, followed by LTMLE, to jointly estimate multiple policies while constraining second-order bias for lower variance.
citing papers explorer
-
Treatment Effect Estimation with Differentiated Networked Effect on Graph Data
A new interference modeling approach with partial attentions and message amplification captures varying neighbor importance and scale to improve ITE estimation on graphs.
-
Smooth Multi-Policy Causal Effect Estimation in Longitudinal Settings
PEQ-Net uses policy-aware reparameterization of ICE Q-functions and kernel mean embeddings in a shared encoder, followed by LTMLE, to jointly estimate multiple policies while constraining second-order bias for lower variance.