NSLab-CUK / Unified-Graph-TransformerLinks
Unified Graph Transformer (UGT) is a novel Graph Transformer model specialised in preserving both local and global graph structures and developed by NS Lab @ CUK based on pure PyTorch backend.
☆27Updated 3 weeks ago
Alternatives and similar repositories for Unified-Graph-Transformer
Users that are interested in Unified-Graph-Transformer are comparing it to the libraries listed below
Sorting:
- Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)☆54Updated 2 years ago
- [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…☆60Updated 2 years ago
- Transformer-based Spectral Graph Neural Networks☆86Updated 10 months ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆31Updated last year
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…☆88Updated last year
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- [ICML 2022] Local Augmentation for Graph Neural Networks☆65Updated last year
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆81Updated 3 years ago
- NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"☆52Updated last year
- Ratioanle-aware Graph Contrastive Learning codebase☆44Updated 2 years ago
- [ICLR 2023] MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization☆77Updated 2 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆60Updated 2 years ago
- PyTorch implementation of GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks☆36Updated 2 years ago
- [NeurIPS'23] Source code of "Data-Centric Learning from Unlabeled Graphs with Diffusion Model": A data-centric transfer learning framewor…☆21Updated 2 months ago
- Implementation of the KDD'24 paper "LPFormer: An Adaptive Graph Transformer for Link Prediction"☆25Updated 2 months ago
- A collection of papers on Graph Structural Learning (GSL)☆55Updated last year
- ☆20Updated 2 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆88Updated 3 years 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
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- Implementation of ICML'24 Paper "Less is More: on the Over-Globalizing Problem in Graph Transformers"☆45Updated last year
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆84Updated 8 months ago
- [ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li☆47Updated 11 months ago
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆87Updated 9 months ago
- Main code for "Revisiting over-smoothing and over-squashing using the Ollivier-Ricci curvature" paper☆17Updated 2 years ago
- The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".☆33Updated 3 years ago
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆128Updated last year
- Graph Masked Autoencoders☆27Updated 2 years ago
- Code for our paper "Attending to Graph Transformers"☆89Updated last year
- [ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs☆100Updated last year