Alternatives and similar repositories for TOGL

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

• beabevi / ESAN
  Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)
  ☆89Updated 2 years ago
• c-hofer / graph_filtration_learning
  ☆22Updated 4 years ago
• BorgwardtLab / WWL
  Wasserstein Weisfeiler-Lehman Graph Kernels
  ☆86Updated last year
• twitter-research / cwn
  Message Passing Neural Networks for Simplicial and Cell Complexes
  ☆164Updated 2 years ago
• vijaydwivedi75 / lrgb
  Long Range Graph Benchmark, NeurIPS 2022 Track on D&B
  ☆160Updated 2 years ago
• luis-mueller / probing-graph-transformers
  Code for our paper "Attending to Graph Transformers"
  ☆92Updated 2 years ago
• lcosmo / DGM_pytorch
  ☆55Updated 3 years ago
• tk-rusch / GraphCON
  GraphCON (ICML 2022)
  ☆59Updated 3 years ago
• cptq / SignNet-BasisNet
  SignNet and BasisNet
  ☆102Updated 2 years ago
• tk-rusch / gradientgating
  Gradient gating (ICLR 2023)
  ☆55Updated 2 years ago
• tech-srl / bottleneck
  Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
  ☆97Updated 3 years ago
• stefaniaebli / simplicial_neural_networks
  Simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called si…
  ☆81Updated 4 years ago
• snap-stanford / conformalized-gnn
  Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)
  ☆84Updated 2 years ago
• mims-harvard / GraphXAI
  GraphXAI: Resource to support the development and evaluation of GNN explainers
  ☆203Updated last year
• twitter-research / neural-sheaf-diffusion
  ☆81Updated 2 years ago
• aidos-lab / pytorch-topological
  A topological machine learning framework based on PyTorch
  ☆197Updated last month
• DevinKreuzer / SAN
  ☆156Updated 4 years ago
• Saro00 / DGN
  Implementation of Directional Graph Networks in PyTorch and DGL
  ☆117Updated 4 years ago
• AlexDuvalinho / GraphSVX
  Explanation method for Graph Neural Networks (GNNs)
  ☆70Updated 7 months ago
• mengliu1998 / awesome-expressive-gnn
  A collection of papers studying/improving the expressiveness of graph neural networks (GNNs)
  ☆124Updated 2 years ago
• jctops / understanding-oversquashing
  ☆42Updated 3 years ago
• pyt-team / TopoModelX
  Topological Deep Learning
  ☆298Updated last week
• 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 2 years ago
• BorgwardtLab / filtration_curves
  Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'
  ☆18Updated 2 years ago
• pyt-team / TopoNetX
  Computing on Topological Domains
  ☆247Updated this week
• saibalmars / GraphRicciCurvature
  A python library to compute the graph Ricci curvature and Ricci flow on NetworkX graph.
  ☆271Updated last year
• vijaydwivedi75 / gnn-lspe
  Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
  ☆265Updated 3 years ago
• twitter-research / graph-neural-pde
  Graph Neural PDEs
  ☆336Updated 3 years ago
• davidbuterez / gnn-neural-readouts
  ☆27Updated 10 months ago
• BorgwardtLab / topological-autoencoders
  Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.
  ☆151Updated 3 years ago