GraphPKU / JacobiConvLinks
How Powerful are Spectral Graph Neural Networks
☆74Updated 2 years ago
Alternatives and similar repositories for JacobiConv
Users that are interested in JacobiConv are comparing it to the libraries listed below
Sorting:
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆107Updated 6 months ago
- ☆139Updated 2 years ago
- Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs☆138Updated 3 years ago
- Graph Structured Neural Network☆40Updated 3 years ago
- ☆42Updated 2 years ago
- [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs☆116Updated 4 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆47Updated 3 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆92Updated 3 years ago
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆58Updated 2 years ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆66Updated last year
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆89Updated 4 years ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆92Updated 4 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆59Updated 4 years ago
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆124Updated 3 years ago
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆81Updated 3 years ago
- Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification☆82Updated 4 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆105Updated last year
- [ICLR'22][KDD'22][IJCAI'24][NeurIPS'25] Implementation of "Graph Condensation for Graph Neural Networks"☆141Updated 2 months ago
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆134Updated last year
- ☆99Updated 4 years ago
- ☆29Updated 4 years ago
- NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"☆52Updated 2 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆87Updated last year
- Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"☆41Updated 2 years ago
- ☆22Updated 3 years ago
- Node Dependent Local Smoothing for Scalable Graph Learning (NeurIPS'21, Spotlight)☆22Updated 3 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- An official PyTorch implementation of "Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels" (WSDM 2022))☆34Updated 3 years ago
- [ICLR 2022] Code for Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation (GLNN)☆95Updated last year
- This repo contains a reference implementation for the paper "Breaking the Limit of Graph Neural Networks by Improving the Assortativity o…☆32Updated 4 years ago