Alternatives and similar repositories for DFNets

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

• chentingpc / gfn
  Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"
  ☆53Updated 5 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆105Updated 6 years ago
• yincheng / GGP
  Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'
  ☆38Updated 7 years ago
• PurdueMINDS / RelationalPooling
  ☆35Updated 6 years ago
• ermongroup / graphite
  Code for Graphite iterative graph generation
  ☆59Updated 6 years ago
• chrsmrrs / sparsewl
  Code for "Weisfeiler and Leman go sparse: Towards higher-order graph embeddings"
  ☆21Updated 4 years ago
• ebonilla / VGCN
  Variational Graph Convolutional Networks
  ☆23Updated 5 years ago
• se-ok / WLsimilarity
  informal exposition of Weisfeiler-Leman similarity
  ☆28Updated 4 years ago
• LingxiaoShawn / PairNorm
  Source code for PairNorm (ICLR 2020)
  ☆79Updated 5 years ago
• vikasverma1077 / GraphMix
  Code for reproducing results in GraphMix paper
  ☆72Updated 3 years ago
• nikhil-dce / SBM-meet-GNN
  Implementation of SBM-meet-GNN
  ☆23Updated 6 years ago
• muhanzhang / D-VAE
  D-VAE: A Variational Autoencoder for Directed Acyclic Graphs, NeurIPS 2019
  ☆145Updated 5 years ago
• PurdueMINDS / Equivalence
  Equivalence Between Structural Representations and Positional Node Embeddings
  ☆22Updated 5 years ago
• cvignac / SMP
  ☆31Updated 4 years ago
• PwnerHarry / Stronger_GCN
  Implementations of "Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks"
  ☆53Updated last year
• matenure / OTCoarsening
  Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport
  ☆37Updated 4 years ago
• bluer555 / KernelGCN
  Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs
  ☆34Updated 5 years ago
• xiaoshuai09 / Wasserstein-Learning-For-Point-Process
  learning point processes by means of optimal transport and wasserstein distance
  ☆54Updated 7 years ago
• balcilar / Spectral-Designed-Graph-Convolutions
  Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper
  ☆50Updated 4 years ago
• hadarser / ProvablyPowerfulGraphNetworks
  ☆16Updated 5 years ago
• lucfra / LDS-GNN
  Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)
  ☆199Updated last year
• HongtengXu / Relational-Factorization-Model
  Gromov-Wasserstein Factorization Models for Graph Clustering (AAAI-20)
  ☆31Updated 3 years ago
• gear / gfnn
  Graph Filter Neural Network (ICPR'20)
  ☆48Updated 5 years ago
• lxiaorui / ElasticGNN
  Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"
  ☆42Updated 4 years ago
• nimadehmamy / Understanding-GCN
  code for the paper in NeurIPS 2019
  ☆40Updated 2 years ago
• amoliu / CayleyNet
  Graph Convolutional Neural Networks with Complex Rational Spectral Filters
  ☆26Updated 7 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆37Updated 5 years ago
• 7qchen / GIND
  Official code of GIND (Optimization-Induced Graph Implicit Nonlinear Diffusion)
  ☆18Updated 3 years ago
• huawei-noah / BGCN
  A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).
  ☆162Updated 6 years ago
• Shen-Lab / SS-GCNs
  [ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
  ☆112Updated 4 years ago