Alternatives and similar repositories for graphkit-learn

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

• BorgwardtLab / WWL
  Wasserstein Weisfeiler-Lehman Graph Kernels
  ☆82Updated 9 months ago
• BorgwardtLab / GraphKernels
  A package for computing Graph Kernels
  ☆104Updated last year
• nd7141 / graph_datasets
  Data for "Understanding Isomorphism Bias in Graph Data Sets" paper.
  ☆89Updated 5 years ago
• chrsmrrs / tudataset
  ☆95Updated 2 years ago
• gbouritsas / GSN
  Official repository for the paper "Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting" (TPAMI'22) https://arxi…
  ☆101Updated 4 years ago
• vunhatminh / PGMExplainer
  Generating PGM Explanation for GNN predictions
  ☆75Updated last year
• BorgwardtLab / P-WL
  A Persistent Weisfeiler–Lehman Procedure for Graph Classification
  ☆61Updated 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
• jacquesfize / GMatch4py
  A graph matching library for Python
  ☆207Updated last year
• snap-stanford / neural-subgraph-learning-GNN
  ☆354Updated last year
• eghisu / GraphKernels
  A package for computing Graph Kernels
  ☆33Updated 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
• leowyy / GraphTSNE
  PyTorch Implementation of GraphTSNE, ICLR’19
  ☆134Updated 6 years ago
• snap-stanford / distance-encoding
  Distance Encoding for GNN Design
  ☆186Updated 4 years ago
• tech-srl / bottleneck
  Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
  ☆94Updated 3 years ago
• kfoynt / LocalGraphClustering
  ☆142Updated 4 years ago
• mims-harvard / SubGNN
  Subgraph Neural Networks (NeurIPS 2020)
  ☆200Updated 4 years ago
• shionhonda / gae-dgl
  Reimplementation of Graph Autoencoder by Kipf & Welling with DGL.
  ☆65Updated 2 years ago
• yunshengb / UGraphEmb
  ☆49Updated 5 years ago
• nd7141 / AWE
  Compute graph embeddings via Anonymous Walk Embeddings
  ☆83Updated 6 years ago
• rusty1s / himp-gnn
  Hierarchical Inter-Message Passing for Learning on Molecular Graphs
  ☆79Updated 3 years ago
• mims-harvard / G-Meta
  Graph meta learning via local subgraphs (NeurIPS 2020)
  ☆123Updated 11 months ago
• snap-stanford / graphwave
  ☆173Updated 6 years ago
• TrustAGI-Lab / graph_datasets
  A Repository of Benchmark Graph Datasets for Graph Classification (31 Graph Datasets In Total).
  ☆290Updated 3 years ago
• TUM-DAML / pprgo_pytorch
  PPRGo model in PyTorch, as proposed in "Scaling Graph Neural Networks with Approximate PageRank" (KDD 2020)
  ☆126Updated 3 years ago
• hugochan / IDGL
  Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddin…
  ☆228Updated last year
• lukecavabarrett / pna
  Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric
  ☆351Updated last week
• SherylHYX / pytorch_geometric_signed_directed
  PyTorch Geometric Signed Directed is a signed/directed graph neural network extension library for PyTorch Geometric. The paper is accepte…
  ☆139Updated 4 months ago
• abojchevski / graph2gauss
  Gaussian node embeddings. Implementation of "Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking".
  ☆174Updated 2 years ago
• lucfra / LDS-GNN
  Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)
  ☆195Updated last year