Alternatives and similar repositories for NetworkDOS:

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

• PurdueMINDS / Equivalence
  Equivalence Between Structural Representations and Positional Node Embeddings
  ☆21Updated 5 years ago
• TheGravLab / A-Unifying-Framework-for-Spectrum-Preserving-Graph-Sparsification-and-Coarsening
  Python code associated with the paper "A Unifying Framework for Spectrum-Preserving Graph Sparsification and Coarsening'' (NeurIPS, 2019)
  ☆16Updated 4 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆35Updated 4 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆103Updated 5 years ago
• nd7141 / AWE
  Compute graph embeddings via Anonymous Walk Embeddings
  ☆82Updated 6 years ago
• ebonilla / VGCN
  Variational Graph Convolutional Networks
  ☆22Updated 4 years ago
• nikhil-dce / SBM-meet-GNN
  Implementation of SBM-meet-GNN
  ☆22Updated 5 years ago
• ermongroup / graphite
  Code for Graphite iterative graph generation
  ☆59Updated 5 years ago
• chentingpc / gfn
  Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"
  ☆51Updated 4 years ago
• twitter-research / sign
  SIGN: Scalable Inception Graph Network
  ☆95Updated 4 years ago
• acbull / LADIES
  Code for NeurIPS'19 "Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks"
  ☆76Updated 2 years ago
• danielzuegner / robust-gcn
  Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".
  ☆42Updated 4 years ago
• bluer555 / KernelGCN
  Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs
  ☆34Updated 5 years ago
• PurdueMINDS / RelationalPooling
  ☆35Updated 5 years ago
• yifan-h / CS-GNN
  Measuring and Improving the Use of Graph Information in Graph Neural Networks
  ☆82Updated 7 months ago
• PurdueMINDS / JanossyPooling
  ☆26Updated 6 years ago
• BorgwardtLab / P-WL
  A Persistent Weisfeiler–Lehman Procedure for Graph Classification
  ☆61Updated 3 years ago
• 000Justin000 / gnn-residual-correlation
  ☆20Updated 3 years ago
• muhanzhang / NestedGNN
  ☆56Updated 3 years ago
• vermaMachineLearning / FGSD
  Graph Feature Representation/Vector Based On The Family Of Graph Spectral Distances (NIPS 2017).
  ☆24Updated 4 years ago
• leichen2018 / GNN-Substructure-Counting
  The official implementation of ''Can Graph Neural Networks Count Substructures?'' NeurIPS 2020
  ☆34Updated 4 years ago
• vwz / AGE
  Active Learning for Graph Embedding
  ☆32Updated 7 years ago
• lxiaorui / ElasticGNN
  Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"
  ☆41Updated 3 years ago
• facebookresearch / NARS
  Scalable Graph Neural Networks for Heterogeneous Graphs
  ☆72Updated 4 years ago
• thu-ml / stochastic_gcn
  Stochastic training of graph convolutional networks
  ☆85Updated 2 years ago
• Haggaim / InvariantGraphNetworks
  Code for the ICLR 2019 paper "Invariant and Equiovariant Graph Networks"
  ☆24Updated 4 years ago
• FFTYYY / TWIRLS
  The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".
  ☆43Updated 3 years ago
• Hanjun-Dai / steady_state_embedding
  Learning Steady-States of Iterative Algorithms over Graphs
  ☆40Updated 6 years ago
• cvignac / SMP
  ☆27Updated 3 years ago
• karl-zhao / benchmarking-gnns-pyg
  ☆30Updated last year