Graph-COM

ED-HNN

[ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li

GAD-NR

[WSDM 2024] GAD-NR : Graph Anomaly Detection via Neighborhood Reconstruction

GraphMaker

code for the paper "GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?"

GSAT

[ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.

LRI

[ICLR 2023] Learnable Randomness Injection (LRI) for interpretable Geometric Deep Learning.

Neighborhood-Aware-Temporal-Network

Yuhong Luo and Pan Li. Neighborhood-aware scalable temporal network representation learning. In Learning on Graphs, 2022.

PEG

StruRW

[ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)

SUREL

[VLDB'22] SUREL is a novel walk-based computation framework for efficient subgraph-based graph representation learning.

SUREL_Plus

[VLDB'23] SUREL+ is a novel set-based computation framework for scalable subgraph-based graph representation learning.

Graph-COM/GSAT

[ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.

Graph-COM/GraphMaker

code for the paper "GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?"

Graph-COM/PEG

Graph-COM/ED-HNN

[ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li

Graph-COM/GAD-NR

[WSDM 2024] GAD-NR : Graph Anomaly Detection via Neighborhood Reconstruction

Graph-COM/Neighborhood-Aware-Temporal-Network

Yuhong Luo and Pan Li. Neighborhood-aware scalable temporal network representation learning. In Learning on Graphs, 2022.

Graph-COM/StruRW

[ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)

Graph-COM/LRI

[ICLR 2023] Learnable Randomness Injection (LRI) for interpretable Geometric Deep Learning.

Graph-COM/SUREL

[VLDB'22] SUREL is a novel walk-based computation framework for efficient subgraph-based graph representation learning.

Graph-COM/CO_ProxyDesign

The repository for 'Unsupervised Learning for Combinatorial Optimization with Principled Proxy Design'

Graph-COM/SUREL_Plus

[VLDB'23] SUREL+ is a novel set-based computation framework for scalable subgraph-based graph representation learning.

Graph-COM/GESS

Code for GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts

Graph-COM/HEPT

[ICML'24 Oral] LSH-Based Efficient Point Transformer (HEPT)

Graph-COM/Neural_Higher-order_Pattern_Prediction

Graph-COM/DIG_MILP

The official implementation of DIG-MILP

Graph-COM/SPE

Official code for SPE

Graph-COM/Pair-Align

[ICML 2024] Code for Pairwise Alignment Improves Graph Domain Adaptation (Pair-Align)

Graph-COM/Bayesian_inference_based_GNN

[Neurips2022] Understanding Non-linearity in Graph Neural Networks from the Perspective of Bayesian Inference

Graph-COM/Meta_CO

the official repository of the paper unsupervised learning for combinatorial optimization needs meta learning

Graph-COM/GSSC

[Preprint] Graph State Space Convolution (GSSC)

Graph-COM/NLB

"No Need to Look Back: An Efficient and Scalable Approach for Temporal Network Representation Learning" by Yuhong Luo and Pan Li

Graph-COM/GAD-EBM

[NeurIPS 2023 : GLFRONTIERS Workshop] GAD-EBM : Graph Anomaly Detection using Energy-Based Models

Graph-COM/Multi-q-Maglap

Graph-COM/xgdl

Explainability Library with Geometric Deep Learning for Scientific Tasks

Graph-COM/Benchmark_for_DGRL_in_Hardwares

The official implementation of `A benchmark for Directed Graph Representation Learning in Hardware Designs'

Graph-COM/a3d3-institute.github.io

draft website using html5up template

Graph-COM/CAW

Graph-COM/distance-encoding

Distance Encoding for GNN Design

Graph-COM/GPRGNN

Graph-COM/Labs-for-Machine-Learning-on-Graphs