AndyJZhao / Gophormer
☆21Updated 2 years ago
Alternatives and similar repositories for Gophormer:
Users that are interested in Gophormer are comparing it to the libraries listed below
- ☆37Updated last year
- ☆42Updated 6 months ago
- NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"☆49Updated last year
- [NeurIPS 2022] The official PyTorch implementation of "Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dyna…☆53Updated 2 years ago
- A pytorch implementation of graph transformer for node classification☆30Updated last year
- Code and dataset for paper "GRAND+: Scalable Graph Random Neural Networks"☆33Updated 2 years ago
- Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".☆31Updated 2 years ago
- NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights☆42Updated 2 months ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 2 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆76Updated 3 months ago
- This repo contains a reference implementation for the paper "Breaking the Limit of Graph Neural Networks by Improving the Assortativity o…☆32Updated 3 years ago
- Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression☆24Updated 11 months ago
- ☆19Updated 2 years ago
- Yuhong Luo and Pan Li. Neighborhood-aware scalable temporal network representation learning. In Learning on Graphs, 2022.☆28Updated last year
- Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"☆37Updated last year
- This is an authors' implementation of the NIPS 2022 dataset and Benchmark Track Paper "A Comprehensive Study on Large Scale Graph Trainin…☆66Updated 2 years ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆28Updated last year
- ☆29Updated 3 years ago
- ☆52Updated 5 months ago
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆53Updated last year
- Node Dependent Local Smoothing for Scalable Graph Learning (NeurIPS'21, Spotlight)☆21Updated 2 years ago
- The official implementation of the paper "Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing" (ICLR 2023).☆43Updated 11 months ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- KDD23 - Classification of Edge-Dependent Labels of Nodes in Hypergraphs☆18Updated 8 months ago
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆109Updated 2 years ago
- ☆16Updated last month
- [ICLR 2023] Link Prediction with Non-Contrastive Learning☆26Updated 2 years ago
- Official repository for NeurIPS'23 paper: GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation☆16Updated last year
- Tail-GNN: Tail-Node Graph Neural Networks☆33Updated 3 years ago
- ☆19Updated 11 months ago