HongtengXu / SGWB-GraphonLinks
Learning Graphons via Structured Gromov-Wasserstein Barycenters
☆22Updated 4 years ago
Alternatives and similar repositories for SGWB-Graphon
Users that are interested in SGWB-Graphon are comparing it to the libraries listed below
Sorting:
- [ICML 2022] pGNN, p-Laplacian Based Graph Neural Networks☆27Updated 3 years ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆115Updated 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
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 4 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆59Updated 2 years ago
- Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"☆38Updated 2 years ago
- [ICLR 2023] "Graph Domain Adaptation via Theory-Grounded Spectral Regularization" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆21Updated 2 years ago
- [ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li☆46Updated 11 months ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 2 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆90Updated 2 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆103Updated 3 weeks ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆169Updated last year
- Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)☆43Updated 2 years ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 4 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
- Papers about developing DL methods on disassortative graphs☆48Updated 3 years ago
- [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☆66Updated last year
- ☆14Updated 3 years ago
- Graph Structured Neural Network☆40Updated 2 years ago
- How Powerful are Spectral Graph Neural Networks☆73Updated last year
- Implementation of the paper "A New Perspective on the Effects of Spectrum in Graph Neural Networks"☆17Updated 3 years ago
- The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…☆21Updated 8 months ago
- Source code for From Stars to Subgraphs (ICLR 2022)☆70Updated last year
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆88Updated 3 years ago
- NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure☆41Updated last year
- Pytorch implementation for ICLR24:"Online GNN Evaluation Under Test-Time Graph Distribution Shifts"☆16Updated last year
- [ICLR 2023] MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization☆77Updated 2 years ago
- This repo is for source code of NeurIPS 2021 paper "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration".☆22Updated 3 years ago
- Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 2021) + Pytorch Implementation of GNN attribution methods☆69Updated 5 months ago