benfinkelshtein / CoGNNLinks
☆58Updated last year
Alternatives and similar repositories for CoGNN
Users that are interested in CoGNN are comparing it to the libraries listed below
Sorting:
- Implementation of ICML'24 Paper "Less is More: on the Over-Globalizing Problem in Graph Transformers"☆46Updated last year
- Transformer-based Spectral Graph Neural Networks☆85Updated last year
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs".☆91Updated last year
- [ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs☆104Updated last year
- A comprehensive benchmark of Graph Structure Learning (NeurIPS 2023 Datasets and Benchmarks Track)☆122Updated last year
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆87Updated last year
- [ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li☆50Updated last year
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆132Updated last year
- A Survey of Learning from Graphs with Heterophily☆154Updated 9 months ago
- NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"☆52Updated 2 years ago
- A collection of papers on Graph Structural Learning (GSL)☆57Updated last year
- [ICML 2022] Local Augmentation for Graph Neural Networks☆66Updated last year
- Official implementation of GraphCLIP: Enhancing Transferability in Graph Foundation Models for Text-Attributed Graphs☆62Updated 9 months ago
- Code for IJCAI'24 paper: Gradformer: Graph Transformer with Exponential Decay☆51Updated last year
- Official Implementation of ICML 2023 paper: "A Generalization of ViT/MLP-Mixer to Graphs"☆167Updated last year
- A curated list of papers on graph structure learning (GSL).☆51Updated 11 months ago
- A collection of graph foundation models including papers, codes, and datasets.☆149Updated 5 months ago
- Code for our paper "Attending to Graph Transformers"☆92Updated 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…☆44Updated last year
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 3 years ago
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆91Updated last year
- A graph transformer framework☆78Updated 3 years ago
- The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classifica…☆314Updated last year
- GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner in WWW'23☆179Updated 2 years ago
- Kolmogorov Arnold Networks (KANs) for Graph Neural Networks (GNNs) and Tasks on Graphs☆66Updated last year
- It is a comprehensive resource hub compiling all graph papers accepted at the International Conference on Learning Representations (ICLR)…☆101Updated last year
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆58Updated 2 years ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆34Updated last year
- PyTorch implementation of "Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited"☆40Updated 2 years ago
- [IJCAI 2024] Papers about graph reduction including graph coarsening, graph condensation, graph sparsification, graph summarization, etc.☆172Updated last month