KevinMoonLab / GRAE
Geometry Regularized Autoencoders (GRAE) for large-scale visualization and manifold learning
☆21Updated last year
Alternatives and similar repositories for GRAE:
Users that are interested in GRAE are comparing it to the libraries listed below
- Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.☆144Updated 3 years ago
- ☆30Updated 2 years ago
- A fully differentiable set autoencoder☆17Updated 11 months ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆44Updated 2 years ago
- Official PyTorch implementation of 🏁 MFCVAE 🏁: "Multi-Facet Clustering Variatonal Autoencoders (MFCVAE)" (NeurIPS 2021). A class of var…☆41Updated last year
- Statistics on the space of asymmetric networks via Gromov-Wasserstein distance☆13Updated 4 years ago
- Official implementation of Joint Multidimensional Scaling☆22Updated last year
- Graph matching and clustering by comparing heat kernels via optimal transport.☆26Updated 2 years ago
- ☆17Updated 6 years ago
- CO-Optimal Transport☆42Updated 4 years ago
- Supplementary code for the AISTATS 2021 paper "Matern Gaussian Processes on Graphs".☆53Updated last month
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆34Updated 4 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- Python3 implementation of the paper [Large-scale optimal transport map estimation using projection pursuit]☆15Updated 4 years ago
- ☆18Updated last year
- ☆38Updated 4 years ago
- Python-based persistent homology algorithms☆19Updated last year
- ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.☆16Updated 7 months ago
- ☆17Updated last year
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆42Updated 2 years ago
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆28Updated 5 years ago
- Pacmed Labs experiments on uncertainty estimation, focusing on unbalanced tabular data and classification tasks.☆21Updated 3 years ago
- Learning the optimal transport map via input convex neural neworks☆41Updated 4 years ago
- Code for Sliced Gromov-Wasserstein☆67Updated 5 years ago
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆85Updated 3 years ago
- Code for JMLR paper ``Learning Representations of Persistence Barcodes``☆23Updated 5 years ago
- Latent optimal transport (LOT) for low rank transport and clustering☆19Updated 3 years ago
- Tensorflow implementation for the SVGP-VAE model.☆22Updated 3 years ago
- DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks☆51Updated last year
- Code for Optimal Transport for structured data with application on graphs☆98Updated 2 years ago