IEEE

ViDR-GNN: Vision Implicit Discriminative Reorganization Graph Neural Networks

Abstract: Vision GNNs (ViGs) divide an image into multiple patches, treating these image patches as graph nodes. The image is represented by extracting explicit features from these patches as node ...
GitHub

verify_pf_gine.m

% using a 3-layer GINE model on the IEEE 118-bus system. W_node1 = double(gather(params.mult1.Weights)); W_node2 = double(gather(params.mult2.Weights)); W_node3 ...
GitHub

verify_pf_gine.m

% using a 3-layer GINE model on the IEEE 39-bus (New England) system. W_node1 = double(gather(params.mult1.Weights)); W_node2 = double(gather(params.mult2.Weights ...
IEEE

GNN-EADD: Graph Neural Network-Based E-Commerce Anomaly Detection via Dual-Stage Learning

Abstract: E-commerce platforms face significant challenges in detecting anomalous products, including counterfeit goods and fraudulent listings, which can undermine user trust and platform integrity.
jech.bmj

Who is the expert? A process guide to incorporate lived/living experience into directed acyclic graphs: an applied example from HIV research

Aim Causal inference relies on correct background knowledge, which epidemiologists generally understand to come from academic experts. Our community-engaged study augments scientific domain knowledge ...