GraphPKU / JacobiConvLinks
How Powerful are Spectral Graph Neural Networks
☆72Updated last year
Alternatives and similar repositories for JacobiConv
Users that are interested in JacobiConv are comparing it to the libraries listed below
Sorting:
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆54Updated 2 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆58Updated 3 years ago
- ☆135Updated last year
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆89Updated 2 years ago
- ☆96Updated 4 years ago
- Node Dependent Local Smoothing for Scalable Graph Learning (NeurIPS'21, Spotlight)☆21Updated 3 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆103Updated last year
- Code and dataset for paper "GRAND+: Scalable Graph Random Neural Networks"☆34Updated 3 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆103Updated 3 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆82Updated 6 months ago
- Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification☆81Updated 4 years ago
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆125Updated last year
- [ICLR 2022] Code for Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation (GLNN)☆89Updated 7 months ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 2 years ago
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆122Updated 2 years ago
- Graph Structured Neural Network☆40Updated 2 years ago
- ☆29Updated 3 years ago
- Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs☆137Updated 2 years ago
- [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"☆138Updated 7 months ago
- ☆76Updated 3 years ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆52Updated 2 years ago
- Papers about developing DL methods on disassortative graphs☆48Updated 2 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆88Updated 3 years ago
- A pytorch implementation of graph transformer for node classification☆31Updated 2 years ago
- ☆57Updated 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))☆33Updated 2 years ago
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- Author: Tong Zhao (tzhao2@nd.edu). ICML 2022. Learning from Counterfactual Links for Link Prediction☆68Updated 2 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