Alternatives and similar repositories for Hypergraph-Tutorial

Users that are interested in Hypergraph-Tutorial are comparing it to the libraries listed below

• ellisalicante / GraphRewiring-Tutorial
  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
• azminewasi / Awesome-Graph-Research-NeurIPS2024
  All graph/GNN papers accepted at NeurIPS 2024.
  ☆81Updated 7 months ago
• XiaoxinHe / neurips2023_learning_on_graphs
  List of papers on NeurIPS2023
  ☆89Updated last year
• GraphFramEx / graphframex
  GraphFramEx: a systematic evaluation framework for explainability methods on GNNs
  ☆44Updated last year
• twitter-research / feature-propagation
  ☆82Updated 3 years ago
• snap-stanford / conformalized-gnn
  Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)
  ☆81Updated last year
• G-Taxonomy-Workgroup / GPSE
  Graph Positional and Structural Encoder
  ☆51Updated 5 months ago
• Graph-COM / GraphMaker
  [TMLR] GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?
  ☆60Updated 2 months ago
• luis-mueller / probing-graph-transformers
  Code for our paper "Attending to Graph Transformers"
  ☆88Updated last year
• AntonioLonga / Explaining-the-Explainers-in-Graph-Neural-Networks
  Repository associated to the paper: "Explaining the Explainers in Graph Neural Networks: a Comparative Study"
  ☆36Updated last year
• giuliacassara / awesome-hypergraph-learning
  A curated list of awesome Hypergraph Learning frameworks, libraries and software.
  ☆22Updated last year
• GraphPKU / PygHO
  A library for subgraph GNN based on pyg
  ☆41Updated 6 months ago
• mengliu1998 / awesome-expressive-gnn
  A collection of papers studying/improving the expressiveness of graph neural networks (GNNs)
  ☆126Updated last year
• melifluos / subgraph-sketching
  code for Graph Neural Networks for Link Prediction with Subgraph Sketching https://arxiv.org/abs/2209.15486
  ☆96Updated last year
• emalgorithm / directed-graph-neural-network
  Dir-GNN is a machine learning model that enables learning on directed graphs.
  ☆81Updated 2 years ago
• AntonioLonga / AdvancePyTorchGeometricTutorials
  here you can find the material used for our Tutorials
  ☆100Updated 3 years ago
• FeiGSSS / Awesome-HigherOrderGraph
  Collection of papers relating data-driven higher-order graph/networks researches.
  ☆70Updated 2 years ago
• RexYing / Rex-Ying-Thesis
  Rex Ying's Ph.D. Thesis, Stanford University
  ☆42Updated 3 years ago
• lrnzgiusti / on-oversquashing
  Official repository for On Over-Squashing in Message Passing Neural Networks (ICML 2023)
  ☆15Updated last year
• DeepGraphLearning / GraphAny
  GraphAny: Fully-inductive Node Classification on Arbitrary Graphs
  ☆140Updated 4 months ago
• RomanBresson / KAGNN
  This is the official repository for our paper KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning.
  ☆43Updated 2 months ago
• toenshoff / LRGB
  ☆21Updated last year
• XiaoxinHe / tape_arxiv_2023
  ☆37Updated last year
• yuwvandy / Large-Graph-Generative-Model
  ☆28Updated 11 months ago
• BenGutteridge / DRew
  ☆31Updated last year
• beabevi / ESAN
  Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)
  ☆89Updated 2 years ago
• AlexDuvalinho / GraphSVX
  Explanation method for Graph Neural Networks (GNNs)
  ☆69Updated last month
• fpour / DGB
  Dynamic Graph Benchmark
  ☆81Updated 2 years ago
• mims-harvard / GraphXAI
  GraphXAI: Resource to support the development and evaluation of GNN explainers
  ☆189Updated last year
• fpour / TGB_Baselines
  TGB baselines for dynamic link property prediction
  ☆23Updated 5 months ago