shagunuppal / Riemannian_Geometry_of_Deep_Generative_ModelsLinks
This repository represents a basic implementation of the paper "Riemannian Geometry of Deep Generative Models", along with the results on two datasets namely MNIST and CelebA.
☆12Updated 5 years ago
Alternatives and similar repositories for Riemannian_Geometry_of_Deep_Generative_Models
Users that are interested in Riemannian_Geometry_of_Deep_Generative_Models are comparing it to the libraries listed below
Sorting:
- Regularized Neural ODEs (RNODE)☆85Updated 4 years ago
- ☆23Updated 4 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆56Updated last year
- ☆68Updated 3 years ago
- PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows☆31Updated 4 years ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆34Updated 4 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆121Updated 2 years ago
- GP Sinkhorn Implementation, paper: https://www.mdpi.com/1099-4300/23/9/1134☆23Updated 3 years ago
- ☆37Updated 5 years ago
- GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021☆52Updated 3 years ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆38Updated 3 years ago
- Stochastic Normalizing Flows☆78Updated 3 years ago
- A minimalist implementation of score-based diffusion model☆129Updated 4 years ago
- ☆54Updated last year
- PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)☆57Updated 2 years ago
- This repository contains code for applying Riemannian geometry in machine learning.☆78Updated 4 years ago
- Implementation of Action Matching for the Schrödinger equation☆24Updated 2 years ago
- ☆31Updated last year
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Transformers with doubly stochastic attention☆48Updated 3 years ago
- Repository for the "Gotta Go Fast When Generating Data with Score-Based Models" paper☆105Updated 3 years ago
- [ICML2022] Variational Wasserstein gradient flow☆24Updated 3 years ago
- Euclidean Wasserstein-2 optimal transportation☆47Updated 2 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆88Updated 2 years ago
- A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation (NeurIPS 2021)☆45Updated 3 years ago
- Library for normalizing flows and neural flows.☆25Updated 3 years ago
- Wavelet Flow: Fast Training of High Resolution Normalizing Flows☆60Updated 4 years ago
- The official code for Efficient Learning of Generative Models via Finite-Difference Score Matching☆12Updated 2 years ago
- A demo shows how to combine Langevin dynamics with score matching for generative models.☆40Updated 4 years ago
- A set of tests for evaluating large-scale algorithms for Wasserstein-1 transport computation (NeurIPS'22).☆21Updated last year