null-xyj / CoBFormerLinks
Implementation of ICML'24 Paper "Less is More: on the Over-Globalizing Problem in Graph Transformers"
☆46Updated last year
Alternatives and similar repositories for CoBFormer
Users that are interested in CoBFormer are comparing it to the libraries listed below
Sorting:
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆130Updated last year
- [ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs☆103Updated last year
- NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"☆52Updated 2 years ago
- A collection of papers on Graph Structural Learning (GSL)☆56Updated last year
- [ICML 2022] Local Augmentation for Graph Neural Networks☆65Updated last year
- [ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li☆48Updated last year
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆86Updated 11 months ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆32Updated last year
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs".☆90Updated last year
- A curated list of papers on graph transfer learning (GTL).☆17Updated 2 years ago
- ☆58Updated 11 months ago
- Ratioanle-aware Graph Contrastive Learning codebase☆43Updated 2 years ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆35Updated 2 years ago
- Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"☆39Updated 2 years ago
- ☆57Updated 3 years ago
- Source code for how powerful are K-hop message passing graph neural networks (Neurips 2022)☆63Updated last year
- A comprehensive benchmark of Graph Structure Learning (NeurIPS 2023 Datasets and Benchmarks Track)☆120Updated last year
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆25Updated 2 years ago
- [NeurIPS'23] Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling. Haotao Wang, Ziyu Jiang, Yuning Y…☆54Updated last year
- ☆42Updated 2 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆45Updated 3 years ago
- Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".☆32Updated 2 years ago
- Official implementation of 'All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining' published i…☆42Updated last year
- Code for AAAI 2023 (Oral) paper "Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting it into MLPs: An Effe…☆26Updated last year
- The implementation for DropMessage.☆37Updated 2 years ago
- ☆22Updated 2 years ago
- Implementation Codes for NeurIPS22 paper "Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift"☆25Updated 2 years ago
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆88Updated 11 months ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- the code of MoG☆19Updated last year