georgiosarvanitidis / geometric_mlLinks
This repository contains code for applying Riemannian geometry in machine learning.
☆78Updated 4 years ago
Alternatives and similar repositories for geometric_ml
Users that are interested in geometric_ml are comparing it to the libraries listed below
Sorting:
- ☆37Updated 5 years ago
- ☆54Updated last year
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Algorithms for computations on random manifolds made easier☆94Updated last year
- Code for the paper: "Independent mechanism analysis, a new concept?"☆24Updated 2 years ago
- Discrete Normalizing Flows implemented in PyTorch☆113Updated 4 years ago
- Official release of code for "Oops I Took A Gradient: Scalable Sampling for Discrete Distributions"☆57Updated 2 years ago
- Regularized Neural ODEs (RNODE)☆84Updated 4 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆57Updated last year
- Official repository for "Categorical Normalizing Flows via Continuous Transformations"☆57Updated 4 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆121Updated 2 years ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆34Updated 4 years ago
- ☆64Updated last year
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆39Updated 3 years ago
- Euclidean Wasserstein-2 optimal transportation☆47Updated 2 years ago
- Manifold-learning flows (ℳ-flows)☆231Updated 5 years ago
- code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".☆129Updated 2 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆44Updated 5 months ago
- Convex potential flows☆84Updated 3 years ago
- Code for paper "SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows"☆288Updated 4 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- PyTorch implementation of Algorithm 1 of "On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models"☆38Updated last year
- Learning the optimal transport map via input convex neural neworks☆42Updated 5 years ago
- ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows☆54Updated 2 years ago
- ☆273Updated 2 years ago
- PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows☆31Updated 4 years ago
- Stochastic Normalizing Flows☆78Updated 3 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 3 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆170Updated 3 years ago