Sep 13, 2024 · We propose CgNN, a novel approach that leverages network structure as instrumental variables (IVs), combined with graph neural networks (GNNs) and attention ...

Sep 13, 2024 · We propose CgNN, a novel approach that leverages network structure as instrumental variables (IVs), combined with graph neural networks (GNNs) and attention ...

Oct 4, 2024 · To address this issue, we propose CgNN, a novel approach that leverages network structure as instrumental variables (IVs), combined with graph ...

Description: The paper aims to enhance causal inference in network data by accurately estimating main, peer, and total causal effects without assuming strong ...

Sep 15, 2024 · This paper introduces Causal GNNs, a novel approach that leverages Graph Neural Networks to enable causal inference in network-structured data.

Sep 16, 2024 · Causal GNNs: A GNN-Driven Instrumental Variable Approach for Causal Inference in Networks https://ift.tt/a8Tlbik · 4:04 AM · Sep 16, 2024.

Sep 16, 2024 · As network data applications continue to expand, causal inference within networks has garnered increasing attention. However, hidden confounders ...

Causal GNNs: A GNN-Driven Instrumental Variable Approach for Causal Inference in Networks ... causal inference within networks has garnered increasing attention.

Sep 23, 2024 · [PDF] Causal GNNs: A GNN-Driven Instrumental Variable Approach for Causal Inference in · Networks. X Du, F Yang, W Gao, X Chen – arXiv preprint ...

Causal GNNs: A GNN-Driven Instrumental Variable Approach for Causal Inference in Networks · no code implementations • 13 Sep 2024 • Xiaojing Du, Feiyu Yang ...