YuxiaWu / SimpleDyGLinks
[WWW 2024] Code and data for "On the Feasibility of Simple Transformer for Dynamic Graph Modeling"
☆32Updated last year
Alternatives and similar repositories for SimpleDyG
Users that are interested in SimpleDyG are comparing it to the libraries listed below
Sorting:
- A Library for Dynamic Graph Learning (NeurIPS 2023)☆276Updated 2 years ago
- "GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection" in NeurIPS 2023☆135Updated last year
- A Survey of Learning from Graphs with Heterophily☆153Updated 9 months ago
- ☆123Updated 2 years ago
- This repository contains the resources on graph neural network (GNN) considering heterophily.☆265Updated last year
- A collection of papers for graph anomaly detection, and published algorithms and datasets.☆132Updated last year
- Codes for ICLR 2024 paper "FreeDyG: Frequency Enhanced Continuous-Time Dynamic Graph Model for Link Prediction"☆36Updated last year
- ☆80Updated last year
- Code for OGC and GGCM☆14Updated last year
- Multi-scale Information Diffusion Prediction with Sequential Hypergraphs☆13Updated last year
- TransGNN, SIGIR 2024☆63Updated last year
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆121Updated 2 years ago
- This is the source code for [SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning]☆15Updated last year
- The official implementation of the paper "Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing" (ICLR 2023).☆47Updated last year
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆87Updated last year
- Data repository for PyGOD☆45Updated last year
- The codes of IJCAI 2021 paper "Temporal Heterogeneous Information Network Embedding"☆15Updated 3 years ago
- code for "Self-supervised representation learning on dynamic graphs"☆27Updated 3 years ago
- Code & data for AAAI'23 Oral paper "Heterogeneous Graph Masked Autoencoders".☆66Updated 2 years ago
- Awesome Temporal Graph Learning is a collection of SOTA, novel temporal graph learning methods (papers, codes, and datasets).☆82Updated 6 months ago
- ☆23Updated last year
- ☆22Updated last year
- PyTorch implementation of "Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomials."☆19Updated 10 months ago
- PyTorch Implementation for "Deep Anomaly Detection on Attributed Networks" (SDM2019)☆75Updated 4 years ago
- [WWW'24] Masked Graph Autoencoder with Non-discrete Bandwidths☆12Updated last year
- Fraud Detection, Low Homophily, Label Utilization, Graph Mining☆50Updated last year
- (WWW 2021) Source code of PC-GNN☆106Updated 3 years ago
- ☆50Updated 2 years ago
- An Empirical Evaluation of Temporal Graph Benchmark☆37Updated 2 years ago
- ☆64Updated 4 years ago