joisino / random-features
Code for "Random Features Strengthen Graph Neural Networks" (SDM 2021)
☆22Updated 4 years ago
Alternatives and similar repositories for random-features:
Users that are interested in random-features are comparing it to the libraries listed below
- Papers about developing DL methods on disassortative graphs☆48Updated 2 years ago
- The implementation of our NeurIPS 2020 paper "Graph Geometry Interaction Learning" (GIL)☆45Updated 4 years ago
- [ICML 2022] pGNN, p-Laplacian Based Graph Neural Networks☆27Updated 2 years ago
- [ICLR 2023] MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization☆77Updated last year
- ☆56Updated 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
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆56Updated last year
- A collection of papers and resources about Data Centric Graph Machine Learning (DC-GML)☆35Updated last year
- Implementation of the paper "A New Perspective on the Effects of Spectrum in Graph Neural Networks"☆17Updated 2 years ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆78Updated 3 years ago
- [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…☆56Updated 2 years ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 3 years ago
- ☆37Updated last year
- A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in …☆30Updated 3 years ago
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 3 years ago
- [ICLR 2023] Link Prediction with Non-Contrastive Learning☆26Updated 2 years ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆66Updated 9 months ago
- Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)☆41Updated 2 years ago
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆81Updated last year
- Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".☆31Updated 2 years ago
- A Note On Over-Smoothing for Graph Neural Network☆20Updated 4 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
- Gradient gating (ICLR 2023)☆53Updated last year
- [ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs☆93Updated last year
- [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"☆134Updated 4 months ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆47Updated 2 years ago
- [VLDB'22] SUREL is a novel walk-based computation framework for efficient subgraph-based graph representation learning.☆19Updated 2 years ago
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆21Updated last year
- Official repository for ICLR'23 paper: Multi-task Self-supervised Graph Neural Network Enable Stronger Task Generalization☆39Updated 2 years ago
- ☆26Updated 3 years ago