Alternatives and similar repositories for pygsp_tutorial_graphsip:

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

• mdbartos / graph-signals
  🕸 Implementations of graph signal processing techniques from "The emerging field of signal processing on graphs" (2013)
  ☆31Updated 6 years ago
• BorgwardtLab / P-WL
  A Persistent Weisfeiler–Lehman Procedure for Graph Classification
  ☆61Updated 3 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆104Updated 5 years ago
• BorgwardtLab / WWL
  Wasserstein Weisfeiler-Lehman Graph Kernels
  ☆81Updated 8 months ago
• rodrigo-pena / graph-learning
  ☆14Updated 7 years ago
• trneedham / Spectral-Gromov-Wasserstein
  Graph matching and clustering by comparing heat kernels via optimal transport.
  ☆26Updated 2 years ago
• paulmorio / geo2dr
  Geo2DR: A Python and PyTorch library for learning distributed representations of graphs.
  ☆46Updated last year
• nimadehmamy / Understanding-GCN
  code for the paper in NeurIPS 2019
  ☆40Updated 2 years ago
• yeze16159 / CurvGN
  Curvature Graph Network
  ☆20Updated 4 years ago
• jwcalder / GraphLearning
  Python package for graph-based clustering and semi-supervised learning
  ☆92Updated last month
• SwiftieH / IGNN
  Implicit Graph Neural Networks
  ☆62Updated 3 years ago
• STAC-USC / Graph_Learning
  Graph Learning from Data
  ☆35Updated 5 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆35Updated 4 years ago
• alelab-upenn / graph-scattering-transforms
  Code for experimentation on graph scattering transforms
  ☆29Updated 5 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
• epfl-lts2 / pygsp
  Graph Signal Processing in Python
  ☆504Updated 2 months 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
• ermongroup / graphite
  Code for Graphite iterative graph generation
  ☆59Updated 5 years ago
• FilippoMB / Benchmark_dataset_for_graph_classification
  Dataset for testing graph classification algorithms, such as Graph Kernels and Graph Neural Networks.
  ☆49Updated last month
• balcilar / gnn-spectral-expressive-power
  Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021
  ☆46Updated 3 years ago
• topology474 / WKPI
  WKPI: A kernel based on persistent homology
  ☆12Updated 4 years ago
• JunwenBai / correlation-gnn
  Correlated Graph Neural Networks
  ☆27Updated 4 years ago
• LingxiaoShawn / PairNorm
  Source code for PairNorm (ICLR 2020)
  ☆76Updated 5 years ago
• zhengdao-chen / GNN4CD
  Supervised community detection with line graph neural networks
  ☆89Updated 4 years ago
• balcilar / Graph_Signal_Processing
  Signal Processing on non-euclidien domain signals
  ☆29Updated 6 years ago
• 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
• tvayer / FGW
  Code for Optimal Transport for structured data with application on graphs
  ☆100Updated 2 years ago
• aGIToz / Graph_Signal_Processing
  Signal processing on graphs using torch_geometric.
  ☆14Updated 2 years ago
• lucfra / LDS-GNN
  Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)
  ☆194Updated last year
• leowyy / GraphTSNE
  PyTorch Implementation of GraphTSNE, ICLR’19
  ☆134Updated 6 years ago