stat-ml / GeoMLELinks
This repo contains code for GeoMLE intrinsic dimension estimation algorithm
☆20Updated 5 years ago
Alternatives and similar repositories for GeoMLE
Users that are interested in GeoMLE are comparing it to the libraries listed below
Sorting:
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆36Updated 5 years ago
- MATLAB code for Stein Point Markov Chain Monte Carlo.☆13Updated 6 years ago
- "Oblique Decision Trees from Derivatives of ReLU Networks" (ICLR 2020, previously called "Locally Constant Networks")☆22Updated 4 years ago
- ☆12Updated 4 years ago
- Code corresponding to the paper Diffusion Earth Mover's Distance and Distribution Embeddings☆37Updated 8 months ago
- ☆30Updated 2 years ago
- Random feature latent variable models in Python☆23Updated 2 years ago
- Graph matching and clustering by comparing heat kernels via optimal transport.☆27Updated 2 years ago
- This is the code related to the article 'Intrinsic persistent homology via density-based metric learning'☆10Updated 2 years ago
- Python code for intrinsic dimension estimation of generic datasets☆19Updated 6 years ago
- Official implementation of NeurIPS'21: Implicit SVD for Graph Representation Learning☆20Updated 3 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆119Updated 2 years ago
- A Python package for intrinsic dimension estimation☆92Updated 3 months ago
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆42Updated 2 years ago
- orbital MCMC☆10Updated 4 years ago
- Deterministic Decoding for Discrete Data in Variational Autoencoders☆24Updated 4 years ago
- Deep Graph Mapper: Seeing Graphs through the Neural Lens☆58Updated 2 years ago
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆29Updated 6 years ago
- Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561☆25Updated 4 years ago
- Differentiable Euler Characteristic Transform☆17Updated last year
- Morgan A. Schmitz., Matthieu Heitz, Nicolas Bonneel, Fred Ngole, David Coeurjolly, Marco Cuturi, Gabriel Peyré, and Jean-Luc Starck. "Was…☆20Updated 5 years ago
- ☆38Updated 5 years ago
- Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.☆150Updated 3 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆35Updated 4 years ago
- Statistics on the space of asymmetric networks via Gromov-Wasserstein distance☆13Updated 5 years ago
- Bayesian optimization with conformal coverage guarantees☆28Updated 2 years ago
- This project provides Slow Feature Analysis as a scikit-learn-style package.☆41Updated last year
- Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)☆50Updated 5 years ago
- SuNBEaM, (s)pectral (n)on-(b)acktracking (e)igenvalue pseudo-(m)etric, a topological graph distance☆15Updated 5 years ago
- NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks☆37Updated 2 years ago