mims-harvard / fastGNMF
Fast graph-regularized matrix factorization
☆20Updated last year
Related projects ⓘ
Alternatives and complementary repositories for fastGNMF
- ☆12Updated 3 years ago
- ☆12Updated 4 years ago
- The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical…☆45Updated last year
- Graph Feature Representation/Vector Based On The Family Of Graph Spectral Distances (NIPS 2017).☆24Updated 4 years ago
- Code for Graph Neural Networks Exponentially Lose Expressive Power for Node Classification.☆30Updated 4 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆35Updated 4 years ago
- Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks☆13Updated 4 years ago
- ☆17Updated 2 years ago
- Morgan A. Schmitz., Matthieu Heitz, Nicolas Bonneel, Fred Ngole, David Coeurjolly, Marco Cuturi, Gabriel Peyré, and Jean-Luc Starck. "Was…☆18Updated 5 years ago
- ☆30Updated last year
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆34Updated 4 years ago
- ☆16Updated 4 years ago
- Software relating to relational empirical risk minimization☆17Updated 3 years ago
- ☆12Updated 3 years ago
- MATLAB implementation of linear support vector classification in hyperbolic space☆21Updated 6 years ago
- The source code of the paper "Understanding Graph Neural Networks from Graph Signal Denoising Perspectives"☆23Updated 4 years ago
- A Python implementation of a fast approximation of the Weisfeiler-Lehman Graph Kernels.☆22Updated 5 years ago
- ☆35Updated 5 years ago
- Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport☆36Updated 3 years ago
- Implementation of Deep Soft-K means☆28Updated 3 years ago
- Implementation of the Multiscale Laplacian Graph Kernel☆18Updated 5 years ago
- Gromov-Wasserstein Factorization Models for Graph Clustering (AAAI-20)☆30Updated 2 years ago
- The implementation of our AAAI 2020 paper "GSSNN: Graph Smoothing Splines Neural Network".☆20Updated 4 years ago
- Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'☆18Updated last year
- Code for core-fringe link prediction☆11Updated 5 years ago
- Code for the paper: "edGNN: A simple and powerful GNN for labeled graphs"☆43Updated last year
- Geo2DR: A Python and PyTorch library for learning distributed representations of graphs.☆45Updated last year
- Equivalence Between Structural Representations and Positional Node Embeddings☆21Updated 4 years ago
- NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks☆36Updated last year