Alternatives and similar repositories for lrgb

Users that are interested in lrgb are comparing it to the libraries listed below

• luis-mueller / probing-graph-transformers
  Code for our paper "Attending to Graph Transformers"
  ☆92Updated 2 years ago
• DevinKreuzer / SAN
  ☆156Updated 4 years ago
• XiaoxinHe / Graph-ViT-MLPMixer
  Official Implementation of ICML 2023 paper: "A Generalization of ViT/MLP-Mixer to Graphs"
  ☆167Updated last year
• vijaydwivedi75 / gnn-lspe
  Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
  ☆267Updated 3 years ago
• RexYing / Rex-Ying-Thesis
  Rex Ying's Ph.D. Thesis, Stanford University
  ☆41Updated 3 years ago
• beabevi / ESAN
  Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)
  ☆90Updated 2 years ago
• LingxiaoShawn / GNNAsKernel
  Source code for From Stars to Subgraphs (ICLR 2022)
  ☆71Updated last year
• jctops / understanding-oversquashing
  ☆42Updated 3 years ago
• lsj2408 / Graphormer-GD
  [ICLR 2023 notable top-5%] Rethinking the Expressive Power of GNNs via Graph Biconnectivity (official implementation)
  ☆105Updated 2 years ago
• XiaoxinHe / neurips2023_learning_on_graphs
  List of papers on NeurIPS2023
  ☆90Updated 2 years ago
• LiamMa / GRIT
  This is an official implementation for "GRIT: Graph Inductive Biases in Transformers without Message Passing".
  ☆129Updated 4 months ago
• mengliu1998 / awesome-expressive-gnn
  A collection of papers studying/improving the expressiveness of graph neural networks (GNNs)
  ☆124Updated 2 years ago
• G-Taxonomy-Workgroup / GPSE
  Graph Positional and Structural Encoder
  ☆54Updated 11 months ago
• divelab / GOOD
  GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]
  ☆204Updated 10 months ago
• Saro00 / DGN
  Implementation of Directional Graph Networks in PyTorch and DGL
  ☆118Updated 4 years ago
• CurryTang / Towards-graph-foundation-models
  ☆91Updated 2 years ago
• tech-srl / bottleneck
  Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
  ☆98Updated 3 years ago
• ucbrise / graphtrans
  Representing Long-Range Context for Graph Neural Networks with Global Attention
  ☆132Updated 3 years ago
• Graph-COM / GSAT
  [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.
  ☆173Updated last year
• hamed1375 / Exphormer
  Exphormer: Sparse Transformer for Graphs
  ☆187Updated last year
• tk-rusch / gradientgating
  Gradient gating (ICLR 2023)
  ☆55Updated 2 years ago
• melifluos / subgraph-sketching
  code for Graph Neural Networks for Link Prediction with Subgraph Sketching https://arxiv.org/abs/2209.15486
  ☆99Updated 2 years ago
• DSL-Lab / Specformer
  Transformer-based Spectral Graph Neural Networks
  ☆85Updated last year
• gbouritsas / GSN
  Official repository for the paper "Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting" (TPAMI'22) https://arxi…
  ☆104Updated 4 years ago
• azminewasi / Awesome-Graph-Research-ICLR2024
  It is a comprehensive resource hub compiling all graph papers accepted at the International Conference on Learning Representations (ICLR)…
  ☆101Updated last year
• XiaoxinHe / icml2023_learning_on_graphs
  List of papers on ICML2023.
  ☆56Updated 2 years ago
• lenscloth / GRPE
  Official Implementation of "GRPE: Relative Positional Encoding for Graph Transformer"
  ☆62Updated 3 years ago
• stadlmax / Graph-Posterior-Network
  Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)
  ☆45Updated 3 years ago
• mims-harvard / GraphXAI
  GraphXAI: Resource to support the development and evaluation of GNN explainers
  ☆203Updated last year
• emalgorithm / directed-graph-neural-network
  Dir-GNN is a machine learning model that enables learning on directed graphs.
  ☆82Updated 2 years ago