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awesome-brain-graph-learning-with-gnns

Awesome graph neural networks for brain network learning. Collections of related research papers with implementations, commonly used datasets and tools. We also invite researchers interested in brain graph learning with GNNs to join the project.

awesome-deep-graph-anomaly-detection

Awesome graph anomaly detection techniques built based on deep learning frameworks. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in anomaly detection, graph representation learning, and graph anomaly detection to join this project as contributors and boost further research in this area.

awesome-diffusion-models-in-medical-imaging

Diffusion Models in Medical Imaging (Published in Medical Image Analysis Journal)

bragcl-framework

An Interpretable Brain Graph Contrastive Learning Framework for Brain Disorder Analysis (WSDM 2024 Demo )

brain-disorder-research

Knowledge Distillation Guided Interpretable Brain Subgraph Neural Networks for Brain Disorder Exploration

brain-image-analysis

Paper list and resources on machine learning for brain image (e. g. fMRI and sMRI) analysis.

brainme

Brain Subgraph Extraction for Disorder Analysis via Cross-Domain Brain Graph Learning

brainmm

Adaptive Multi-Modal and Multi-Attribute Brain Graph Learning for Brain Disorder Analysis

comga

The paper " ComGA:Community-Aware Attributed Graph Anomaly Detection" was accepted by WSDM 2022.

dsnr

The paper "Deep Semantic Network Representation" was accepted by ICDM 2020.

figure-survey

gladc

The paper "Deep Graph Level Anomaly Detection with Contrastive Learning" has been accepted by Scientific Reports Journal.

graph-information-bottleneck-for-subgraph-recognition

kdd2024-rebuttal

moepg

The paper "Reinforcement Learning Guided Multi-Objective Exam Paper Generation " was accepted by SDM 2023.

reipool

ReiPool: Reinforced Pooling Graph Neural Networks for Graph-Level Representation Learning

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