twitter-research / feature-propagationLinks
☆82Updated 3 years ago
Alternatives and similar repositories for feature-propagation
Users that are interested in feature-propagation are comparing it to the libraries listed below
Sorting:
- PyTorch Geometric Signed Directed is a signed/directed graph neural network extension library for PyTorch Geometric. The paper is accepte…☆142Updated 5 months ago
- Temporal Graph Benchmark project repo☆227Updated last month
- Dynamic Graph Benchmark☆81Updated 2 years ago
- Code for our paper "Attending to Graph Transformers"☆89Updated last year
- GraphXAI: Resource to support the development and evaluation of GNN explainers☆192Updated last year
- This repository holds code and other relevant files for the Learning on Graphs 2022 tutorial "Graph Rewiring: From Theory to Applications…☆54Updated 2 years ago
- ☆60Updated 3 years ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 4 years ago
- GraphFramEx: a systematic evaluation framework for explainability methods on GNNs☆44Updated last year
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆80Updated last year
- code for Graph Neural Networks for Link Prediction with Subgraph Sketching https://arxiv.org/abs/2209.15486☆96Updated last year
- Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)☆83Updated last year
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆94Updated 3 years ago
- ☆75Updated 2 years ago
- ☆138Updated 4 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆88Updated 3 years ago
- Generating PGM Explanation for GNN predictions☆75Updated 2 years ago
- [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs☆113Updated 3 years ago
- A collection of papers studying/improving the expressiveness of graph neural networks (GNNs)☆126Updated last year
- Official repository for the paper "Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting" (TPAMI'22) https://arxi…☆101Updated 4 years ago
- Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."☆67Updated 3 years ago
- Dir-GNN is a machine learning model that enables learning on directed graphs.☆81Updated 2 years ago
- here you can find the material used for our Tutorials☆101Updated 3 years ago
- Explanation method for Graph Neural Networks (GNNs)☆69Updated 2 months ago
- A curated list of graph data augmentation papers.☆311Updated last year
- TGB baselines for dynamic link property prediction☆23Updated 6 months ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆103Updated 3 weeks ago
- ☆95Updated 2 years ago
- ☆19Updated 2 years ago
- Long Range Graph Benchmark, NeurIPS 2022 Track on D&B☆157Updated last year