jason9464's Stars
flyingdoog/awesome-graph-explainability-papers
Papers about explainability of GNNs
Cyrus9721/Characterizing_graph_influence
chom5621/AlignDiff
Data-Centric-GraphML/awesome-papers
A collection of papers and resources about Data-centric Graph Machine Learning (DC-GML).
ml-postech/reverse-gnn
LechengKong/OneForAll
A fundational graph learning framework that solves cross-domain/cross-task classification problems using one model.
XiaoxinHe/Awesome-Graph-LLM
A collection of AWESOME things about Graph-Related LLMs.
Godofnothing/HeterophilySpecificModels
alexfanjn/Graph-Neural-Networks-With-Heterophily
This repository contains the resources on graph neural network (GNN) considering heterophily.
LUMIA-Group/OrderedGNN
The official implementation of the paper "Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing" (ICLR 2023).
gdmnl/LD2
The origianl code for "LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embeddings", NeurIPS 2023
sunjss/CoCN
Official implementation of Compressed Convolution Networks (CoCNs), including the source code for the ICML 2023 paper "All in a Row: Compressed Convolution Networks for Graphs".
Jinx-byebye/LRGNN
Official implementation of NeurIPS 2023 paper "Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily"
yandex-research/heterophilous-graphs
A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?
jules-leguy/EvoMol
Evolutionary algorithm for molecular properties optimization
lsh0520/RGCL
Ratioanle-aware Graph Contrastive Learning codebase
jajupmochi/graphkit-learn
A python package for graph kernels, graph edit distances, and graph pre-image problem.
ysig/GraKeL
A scikit-learn compatible library for graph kernels
PyGCL/PyGCL
PyGCL: A PyTorch Library for Graph Contrastive Learning
Shen-Lab/GraphCL
[NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen
LirongWu/awesome-graph-self-supervised-learning
Code for TKDE paper "Self-supervised learning on graphs: Contrastive, generative, or predictive"
liugangcode/GREA
[KDD'22] Source codes of "Graph Rationalization with Environment-based Augmentations"
Lin-Yijie/Graph-Matching-Networks
PyTorch implementation of Graph Matching Networks, e.g., Graph Matching with Bi-level Noisy Correspondence (COMMON, ICCV 2023), Graph Matching Networks for Learning the Similarity of Graph Structured Objects (GMN, ICML 2019).
beabevi/ESAN
Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)
jeanfeydy/geomloss
Geometric loss functions between point clouds, images and volumes
PythonOT/POT
POT : Python Optimal Transport
priba/graph_metric.pytorch
Graph Metric Learning in PyTorch
snudatalab/GraphAug
Model-Agnostic Augmentation for Accurate Graph Classification (WWW 2022)
ahxt/g-mixup
[ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification
diningphil/gnn-comparison
Official Repository of "A Fair Comparison of Graph Neural Networks for Graph Classification", ICLR 2020