Pinned Repositories
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
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.
GLADC
The paper "Deep Graph Level Anomaly Detection with Contrastive Learning" has been accepted by Scientific Reports Journal.
graph-information-bottleneck-for-Subgraph-Recognition
ReiPool
ReiPool: Reinforced Pooling Graph Neural Networks for Graph-Level Representation Learning
XuexiongLuoMQ's Repositories
XuexiongLuoMQ/ComGA
The paper " ComGA:Community-Aware Attributed Graph Anomaly Detection" was accepted by WSDM 2022.
XuexiongLuoMQ/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.
XuexiongLuoMQ/GLADC
The paper "Deep Graph Level Anomaly Detection with Contrastive Learning" has been accepted by Scientific Reports Journal.
XuexiongLuoMQ/DSNR
The paper "Deep Semantic Network Representation" was accepted by ICDM 2020.
XuexiongLuoMQ/BraGCL-framework
An Interpretable Brain Graph Contrastive Learning Framework for Brain Disorder Analysis (WSDM 2024 Demo )
XuexiongLuoMQ/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.
XuexiongLuoMQ/graph-information-bottleneck-for-Subgraph-Recognition
XuexiongLuoMQ/ReiPool
ReiPool: Reinforced Pooling Graph Neural Networks for Graph-Level Representation Learning
XuexiongLuoMQ/Awesome-Diffusion-Models-in-Medical-Imaging
Diffusion Models in Medical Imaging (Published in Medical Image Analysis Journal)
XuexiongLuoMQ/brain-disorder-research
Knowledge Distillation Guided Interpretable Brain Subgraph Neural Networks for Brain Disorder Exploration
XuexiongLuoMQ/Brain-Image-Analysis
Paper list and resources on machine learning for brain image (e. g. fMRI and sMRI) analysis.
XuexiongLuoMQ/BrainME
Brain Subgraph Extraction for Disorder Analysis via Cross-Domain Brain Graph Learning
XuexiongLuoMQ/BrainMM
Adaptive Multi-Modal and Multi-Attribute Brain Graph Learning for Brain Disorder Analysis
XuexiongLuoMQ/figure-survey
XuexiongLuoMQ/KDD2024-Rebuttal
XuexiongLuoMQ/MOEPG
The paper "Reinforcement Learning Guided Multi-Objective Exam Paper Generation " was accepted by SDM 2023.
XuexiongLuoMQ/XuexiongLuoMQ.github.io