Alternatives and similar repositories for graphkit-learn:

Users that are interested in graphkit-learn are comparing it to the libraries listed below

• BorgwardtLab / GraphKernels
  A package for computing Graph Kernels
  ☆104Updated last year
• BorgwardtLab / WWL
  Wasserstein Weisfeiler-Lehman Graph Kernels
  ☆81Updated 8 months ago
• eghisu / GraphKernels
  A package for computing Graph Kernels
  ☆33Updated 6 years ago
• jacquesfize / GMatch4py
  A graph matching library for Python
  ☆204Updated last year
• kfoynt / LocalGraphClustering
  ☆138Updated 4 years ago
• shionhonda / gae-dgl
  Reimplementation of Graph Autoencoder by Kipf & Welling with DGL.
  ☆65Updated 2 years ago
• snap-stanford / neural-subgraph-learning-GNN
  ☆351Updated 10 months ago
• nd7141 / graph_datasets
  Data for "Understanding Isomorphism Bias in Graph Data Sets" paper.
  ☆89Updated 5 years ago
• BorgwardtLab / P-WL
  A Persistent Weisfeiler–Lehman Procedure for Graph Classification
  ☆61Updated 3 years ago
• leowyy / GraphTSNE
  PyTorch Implementation of GraphTSNE, ICLR’19
  ☆134Updated 6 years ago
• chrsmrrs / k-gnn
  Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".
  ☆187Updated 3 years ago
• chrsmrrs / tudataset
  ☆94Updated 2 years ago
• deezer / linear_graph_autoencoders
  Source code from the NeurIPS 2019 workshop article "Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks" (G. Salha, R…
  ☆132Updated 4 years ago
• ysig / GraKeL
  A scikit-learn compatible library for graph kernels
  ☆616Updated 6 months ago
• tech-srl / bottleneck
  Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
  ☆94Updated 3 years ago
• mims-harvard / SubGNN
  Subgraph Neural Networks (NeurIPS 2020)
  ☆194Updated 4 years ago
• hugochan / IDGL
  Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddin…
  ☆227Updated last year
• baldassarreFe / graph-network-explainability
  Explainability techniques for Graph Networks, applied to a synthetic dataset and an organic chemistry task. Code for the workshop paper "…
  ☆122Updated 5 years ago
• GemsLab / REGAL
  Representation learning-based graph alignment based on implicit matrix factorization and structural embeddings
  ☆95Updated 4 years ago
• Dru-Mara / EvalNE
  Source code for EvalNE, a Python library for evaluating Network Embedding methods.
  ☆106Updated last year
• danielzuegner / netgan
  Implementation of the paper "NetGAN: Generating Graphs via Random Walks".
  ☆194Updated 4 years ago
• beabevi / ESAN
  Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)
  ☆89Updated last year
• FilippoMB / Spectral-Clustering-with-Graph-Neural-Networks-for-Graph-Pooling
  Reproduces the results of MinCutPool as presented in the 2020 ICML paper "Spectral Clustering with Graph Neural Networks for Graph Poolin…
  ☆271Updated last month
• AlexDuvalinho / GraphSVX
  Explanation method for Graph Neural Networks (GNNs)
  ☆68Updated last week
• shchur / overlapping-community-detection
  Implementation of "Overlapping Community Detection with Graph Neural Networks"
  ☆164Updated 4 years ago
• dkaslovsky / GraphRole
  Automatic feature extraction and node role assignment for transfer learning on graphs (ReFeX & RolX)
  ☆86Updated 9 months ago
• xgfs / NetLSD
  NetLSD descriptors for graphs. Compare and analyze graph structure on multiple levels!
  ☆59Updated 5 years ago
• snap-stanford / graphwave
  ☆172Updated 6 years ago
• sunfanyunn / InfoGraph
  Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" …
  ☆319Updated last year
• benedekrozemberczki / RolX
  An alternative implementation of Recursive Feature and Role Extraction (KDD11 & KDD12)
  ☆70Updated 2 years ago