IEEE

Graph Convolution for Large-Scale Graph Node Classification Task Based on Spatial and Frequency Domain Fusion

Abstract: In recent years, Graph Neural Networks (GNNs) have achieved significant success in graph-based tasks. However, they still face challenges in complex scenarios, particularly in integrating ...
GitHub

A JAX backend for Apple Metal Performance Shaders (MPS), enabling GPU-accelerated JAX computations on Apple Silicon.

jax-mps achieves a modest 3x speed-up over the CPU backend when training a simple ResNet18 model on CIFAR-10 using an M4 MacBook Air. The plugin registers itself with JAX automatically and is enabled ...
GitHub

Aggregate to Adapt: Node-Centric Aggregation for Multi-Source-Free Graph Domain Adaptation (WWW-2025).

This is a PyTorch implementation of the GraphATA algorithm, which tries to address the multi-source domain adaptation problem without accessing the labelled source graph. Unlike previous multi-source ...
IEEE

GZOO: Black-Box Node Injection Attack on Graph Neural Networks via Zeroth-Order Optimization

Abstract: The ubiquity of Graph Neural Networks (GNNs) emphasizes the imperative to assess their resilience against node injection attacks, a type of evasion attacks that impact victim models by ...