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 6 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:
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆57Updated last year
- ☆68Updated 3 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆122Updated 2 years ago
- ☆23Updated 4 years ago
- GP Sinkhorn Implementation, paper: https://www.mdpi.com/1099-4300/23/9/1134☆23Updated 3 years ago
- PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows☆31Updated 4 years ago
- Convex potential flows☆84Updated 4 years ago
- Wavelet Flow: Fast Training of High Resolution Normalizing Flows☆60Updated 4 years ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆34Updated 4 years ago
- Stochastic Normalizing Flows☆78Updated 4 years ago
- ☆21Updated 3 years ago
- Regularized Neural ODEs (RNODE)☆81Updated 4 years ago
- ☆33Updated 3 years ago
- Repository for the "Gotta Go Fast When Generating Data with Score-Based Models" paper☆105Updated 4 years ago
- This repository contains code for applying Riemannian geometry in machine learning.☆78Updated 4 years ago
- ☆29Updated 4 years ago
- A minimalist implementation of score-based diffusion model☆129Updated 4 years ago
- Probabilistic Auto-Encoder☆43Updated 2 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆88Updated 3 years ago
- Manifold-learning flows (ℳ-flows)☆231Updated 5 years ago
- Code repository of the paper "Wavelet Networks: Scale-Translation Equivariant Learning From Raw Time-Series, TMLR" https://arxiv.org/abs…☆83Updated last year
- ☆54Updated last year
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆39Updated 3 years ago
- [ICML2022] Variational Wasserstein gradient flow☆24Updated 3 years ago
- ☆21Updated 5 years ago
- Library for normalizing flows and neural flows.☆25Updated 3 years ago
- Code for 'Periodic Activation Functions Induce Stationarity' (NeurIPS 2021)☆19Updated 4 years ago
- GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021☆54Updated 3 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 3 years ago
- Implementation of normalizing flows in TensorFlow 2 including a small tutorial.☆146Updated 2 months ago