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
  ☆103Updated last year
• BorgwardtLab / WWL
  Wasserstein Weisfeiler-Lehman Graph Kernels
  ☆81Updated 5 months ago
• nd7141 / graph_datasets
  Data for "Understanding Isomorphism Bias in Graph Data Sets" paper.
  ☆89Updated 5 years ago
• TrustAGI-Lab / graph_datasets
  A Repository of Benchmark Graph Datasets for Graph Classification (31 Graph Datasets In Total).
  ☆288Updated 2 years ago
• eghisu / GraphKernels
  A package for computing Graph Kernels
  ☆33Updated 6 years ago
• BorgwardtLab / P-WL
  A Persistent Weisfeiler–Lehman Procedure for Graph Classification
  ☆60Updated 3 years ago
• chrsmrrs / tudataset
  ☆92Updated last year
• kfoynt / LocalGraphClustering
  ☆137Updated 3 years ago
• edouardpineau / A-simple-baseline-algorithm-for-graph-classification
  Github page for the paper "A simple baseline algorithm for graph classification" presented at the R2L workshop of NIPS 2018
  ☆25Updated 4 years ago
• gbouritsas / GSN
  Official repository for the paper "Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting" (TPAMI'22) https://arxi…
  ☆100Updated 3 years ago
• vunhatminh / PGMExplainer
  Generating PGM Explanation for GNN predictions
  ☆74Updated last year
• sunfanyunn / graph-classification
  A collection of graph classification methods
  ☆42Updated 4 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
• chrsmrrs / k-gnn
  Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".
  ☆185Updated 2 years ago
• jacquesfize / GMatch4py
  A graph matching library for Python
  ☆198Updated 9 months ago
• snap-stanford / neural-subgraph-learning-GNN
  ☆348Updated 7 months ago
• yunshengb / GraphSim
  ☆52Updated 5 years ago
• lukasjf / contrastive-gnn-explanation
  ☆19Updated 2 years ago
• 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
• snap-stanford / distance-encoding
  Distance Encoding for GNN Design
  ☆187Updated 3 years ago
• rusty1s / himp-gnn
  Hierarchical Inter-Message Passing for Learning on Molecular Graphs
  ☆77Updated 3 years ago
• yunshengb / UGraphEmb
  ☆47Updated 5 years ago
• leowyy / GraphTSNE
  PyTorch Implementation of GraphTSNE, ICLR’19
  ☆134Updated 5 years ago
• davidbuterez / gnn-neural-readouts
  ☆27Updated last month
• tech-srl / bottleneck
  Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
  ☆94Updated 2 years ago
• DongqiFu / DPPIN
  DPPIN: A Biological Repository of Dynamic Protein-Protein Interaction Network Data, IEEE BigData 2022
  ☆27Updated 2 years ago
• hugochan / IDGL
  Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddin…
  ☆226Updated last year
• nd7141 / AWE
  Compute graph embeddings via Anonymous Walk Embeddings
  ☆82Updated 6 years ago
• abojchevski / graph2gauss
  Gaussian node embeddings. Implementation of "Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking".
  ☆175Updated last year
• shionhonda / gae-dgl
  Reimplementation of Graph Autoencoder by Kipf & Welling with DGL.
  ☆66Updated 2 years ago