orybkin / sigma-vae-pytorchLinks
A σ-VAE implementation in PyTorch
☆99Updated 3 years ago
Alternatives and similar repositories for sigma-vae-pytorch
Users that are interested in sigma-vae-pytorch are comparing it to the libraries listed below
Sorting:
- Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)☆84Updated 2 years ago
- Implementation of Flow++ in PyTorch☆40Updated 6 years ago
- Pytorch Implementation of OpenAI's "Improved Variational Inference with Inverse Autoregressive Flow"☆83Updated 5 years ago
- Unofficial Implementation of "Denoising Diffusion Probabilistic Models" in PyTorch(Lightning)☆91Updated 5 years ago
- ☆148Updated 3 years ago
- An unofficial toy implementation for NVAE 《A Deep Hierarchical Variational Autoencoder》☆113Updated 4 years ago
- Repository for the "Gotta Go Fast When Generating Data with Score-Based Models" paper☆105Updated 3 years ago
- Code for reproducing Flow ++ experiments☆189Updated 6 years ago
- Official code for "Maximum Likelihood Training of Score-Based Diffusion Models", NeurIPS 2021 (spotlight)☆150Updated 3 years ago
- Repository for the paper "Simple and Effective VAE Training with Calibrated Decoders"☆29Updated 4 years ago
- A minimalist implementation of score-based diffusion model☆129Updated 4 years ago
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆69Updated 4 years ago
- Implicit Generation and Generalization in Energy Based Models in PyTorch☆66Updated 6 years ago
- Denoising Diffusion Implicit Models☆28Updated 4 years ago
- A PyTorch implementation of "Continuous Relaxation Training of Discrete Latent Variable Image Models"☆74Updated 5 years ago
- [Neurips 2021]Diffusion Normalizing Flow (DiffFlow)☆118Updated 2 years ago
- Implementation and tutorials of normalizing flows with the novel distributions module☆168Updated 5 years ago
- Code for paper "SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows"☆288Updated 4 years ago
- Ladder Variational Autoencoders (LVAE) in PyTorch☆92Updated 5 years ago
- ☆68Updated 2 years ago
- Conditional Generative model (Normalizing Flow) and experimenting style transfer using this model☆79Updated 2 years ago
- ☆124Updated 2 years ago
- ☆26Updated 6 years ago
- ☆52Updated 4 years ago
- Gradient Origin Networks - a new type of generative model that is able to quickly learn a latent representation without an encoder☆159Updated 4 years ago
- The Official PyTorch Implementation of "VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models" (ICLR 2021 spotlight…☆57Updated 3 years ago
- Code for ICLR 2021 Paper, "Anytime Sampling for Autoregressive Models via Ordered Autoencoding"☆26Updated 2 years ago
- Official code for "VFlow: More Expressive Generative Flows with Variational Data Augmentation" (ICML 2020)☆40Updated 2 years ago
- Nonlinear Independent Components Estimation (Dinh et al, 2014) in PyTorch.☆122Updated 6 years ago
- PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)☆57Updated 2 years ago