vlivashkin / pygkernelsLinks
Graphs clustering using kernel measures and estimators. Kernel KMeans, Spectral Clustering, Kernel Ward etc.
☆18Updated last year
Alternatives and similar repositories for pygkernels
Users that are interested in pygkernels are comparing it to the libraries listed below
Sorting:
- Graph matching and clustering by comparing heat kernels via optimal transport.☆26Updated 2 years ago
- Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching☆43Updated 5 years ago
- Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'☆38Updated 6 years ago
- Neural Dynamics on Complex Networks☆53Updated 4 years ago
- This repository holds code and other relevant files for the Learning on Graphs 2022 tutorial "Graph Rewiring: From Theory to Applications…☆54Updated 2 years ago
- wNMF: Weighted Non-Negative Matrix Factorization☆17Updated last year
- Source code from the CIKM 2019 article "Gravity-Inspired Graph Autoencoders for Directed Link Prediction" by G. Salha, S. Limnios, R. Hen…☆46Updated last year
- Code for the paper "RWR-GAE: Random Walk Regularized Graph Auto Encoder"☆38Updated last year
- Wasserstein Weisfeiler-Lehman Graph Kernels☆82Updated 9 months ago
- Official implementation of Joint Multidimensional Scaling☆22Updated last year
- SG-EDNE: Skip-Gram based Ensembles Dynamic Network Embedding (for our paper "Robust Dynamic Network Embedding via Ensembles")☆10Updated 3 years ago
- ☆20Updated 4 years ago
- Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch☆60Updated 4 years ago
- Experimental Matlab code for methods and some examples in "Higher-order organization of complex networks"☆41Updated 6 years ago
- the Implementation of "Structural Deep Embedding for Hyper-Networks"（AAA20I8）☆46Updated 6 years ago
- Collection of papers relating data-driven higher-order graph/networks researches.☆71Updated 2 years ago
- Supervised community detection with line graph neural networks☆89Updated 4 years ago
- Hypergraph representation learning: Hypergraph Networks with Hyperedge Neurons.☆41Updated 4 years ago
- ☆138Updated 4 years ago
- Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."☆66Updated 3 years ago
- GraphFramEx: a systematic evaluation framework for explainability methods on GNNs☆44Updated last year
- A Pytorch implementation of Semi-implicit-graph-variational-auto-encoders☆14Updated 5 years ago
- Tensorflow 2.0 implementation of "Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning" in ICCV2019☆45Updated 5 years ago
- ☆47Updated 3 years ago
- ☆28Updated 3 years ago
- A sparsity aware implementation of "Biological Network Comparison Using Graphlet Degree Distribution" (Bioinformatics 2007)☆26Updated 2 years ago
- Generating PGM Explanation for GNN predictions☆75Updated last year
- Wasserstein Distance Graph Alignment☆23Updated 4 years ago
- Code for Graphite iterative graph generation☆59Updated 6 years ago
- Algorithms for learning network structure from effective resistances and other random-walk-based similarities.☆31Updated 7 years ago