Alternatives and similar repositories for PygHO

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

• luis-mueller / probing-graph-transformers
  Code for our paper "Attending to Graph Transformers"
  ☆90Updated last year
• G-Taxonomy-Workgroup / GPSE
  Graph Positional and Structural Encoder
  ☆53Updated 7 months ago
• Chen-Cai-OSU / MPNN-GT-Connection
  ☆21Updated 2 years ago
• KarolisMart / SPECTRE
  Reference implementation for SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators (ICML …
  ☆26Updated 3 years ago
• BenGutteridge / DRew
  ☆31Updated last year
• jctops / understanding-oversquashing
  ☆41Updated 3 years ago
• toenshoff / LRGB
  ☆22Updated last year
• RomanBresson / KAGNN
  This is the official repository for our paper KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning.
  ☆44Updated 5 months ago
• vijaydwivedi75 / lrgb
  Long Range Graph Benchmark, NeurIPS 2022 Track on D&B
  ☆158Updated last year
• tk-rusch / gradientgating
  Gradient gating (ICLR 2023)
  ☆53Updated 2 years ago
• RexYing / Rex-Ying-Thesis
  Rex Ying's Ph.D. Thesis, Stanford University
  ☆41Updated 3 years ago
• LiamMa / GRIT
  This is an official implementation for "GRIT: Graph Inductive Biases in Transformers without Message Passing".
  ☆126Updated 3 weeks ago
• beabevi / SUN
  Understanding and Extending Subgraph GNNs by Rethinking their Symmetries (NeurIPS 2022 Oral)
  ☆41Updated 2 years ago
• shamim-hussain / egt_pytorch
  Edge-Augmented Graph Transformer
  ☆78Updated last year
• azminewasi / Awesome-Graph-Research-NeurIPS2024
  All graph/GNN papers accepted at NeurIPS 2024.
  ☆83Updated 10 months ago
• LingxiaoShawn / GNNAsKernel
  Source code for From Stars to Subgraphs (ICLR 2022)
  ☆69Updated last year
• FilippoMB / The-expressive-power-of-pooling-in-GNNs
  Code and dataset to test empirically the expressive power of graph pooling operators presented as presented at NeurIPS 2023
  ☆36Updated last year
• snap-stanford / conformalized-gnn
  Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)
  ☆82Updated last year
• beabevi / ESAN
  Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)
  ☆89Updated 2 years ago
• lsj2408 / Graphormer-GD
  [ICLR 2023 notable top-5%] Rethinking the Expressive Power of GNNs via Graph Biconnectivity (official implementation)
  ☆103Updated 2 years ago
• lenscloth / GRPE
  Official Implementation of "GRPE: Relative Positional Encoding for Graph Transformer"
  ☆61Updated 3 years ago
• ykiiiiii / ACMP
  ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks(ICLR 2023)
  ☆20Updated last year
• azminewasi / Awesome-Graph-Research-ICLR2025
  It is a comprehensive resource hub compiling all graph papers accepted at the International Conference on Learning Representations (ICLR)…
  ☆41Updated 6 months ago
• jiaqingxie / Theories-of-Graph-Neural-Networks
  A List of Papers on Theoretical Foundations of Graph Neural Networks
  ☆36Updated 5 months ago
• Chen-Cai-OSU / GNN-Over-Smoothing
  A Note On Over-Smoothing for Graph Neural Network
  ☆20Updated 5 years ago
• XiaoxinHe / neurips2023_learning_on_graphs
  List of papers on NeurIPS2023
  ☆89Updated last year
• DSL-Lab / Specformer
  Transformer-based Spectral Graph Neural Networks
  ☆85Updated 11 months ago
• uoguelph-mlrg / GGM-metrics
  Official repository for the paper "On Evaluation Metrics for Graph Generative Models"
  ☆25Updated 3 years ago
• Graph-COM / Pair-Align
  [ICML 2024] Code for Pairwise Alignment Improves Graph Domain Adaptation (Pair-Align)
  ☆14Updated last year
• emalgorithm / directed-graph-neural-network
  Dir-GNN is a machine learning model that enables learning on directed graphs.
  ☆81Updated 2 years ago