Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
-
Updated
Jul 31, 2024 - Python
Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
Optimus: the first large-scale pre-trained VAE language model
[CVPR 2021 Oral] Official PyTorch implementation of Soft-IntroVAE from the paper "Soft-IntroVAE: Analyzing and Improving Introspective Variational Autoencoders"
VAE with RealNVP prior and Super-Resolution VAE in PyTorch. Code release for https://arxiv.org/abs/2006.05218.
Generative models (GAN, VAE, Diffusion Models, Autoregressive Models) implemented with Pytorch, Pytorch_lightning and hydra.
moai is a PyTorch-based AI Model Development Kit (MDK) created to improve data-driven model workflows, design and reproducibility.
Official PyTorch implementation of A Quaternion-Valued Variational Autoencoder (QVAE).
🤖 | Learning PyTorch through official examples
Pytorch implementation of GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection
Dirichlet-Variational Auto-Encoder by PyTorch
Codebase for the paper: Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts
A Variational Autoencoder in PyTorch for the CelebA Dataset.
Deep Learning And Applied Artificial Intelligence Project 2019/2020 - Molecular Synthesis & Reconstruction
Pytorch implementation of a Variational Autoencoder (VAE) that learns from the MNIST dataset and generates images of altered handwritten digits.
Pytorch implementation of Gaussian Mixture Variational Autoencoder GMVAE
This repository contains code for VAE and CVAE using residual and inverse residual blocks
Variational Autoencoder (VAE)-based molecular SMILES string generator
Notes about the video on the Variational Autoencoder
Codes for paper: CVQVAE: A REPRESENTATION LEARNING METHOD FOR MULTI-OMICS SINGLE CELL DATA INTEGRATION
A collection of research paper implementations in PyTorch
Add a description, image, and links to the vae-pytorch topic page so that developers can more easily learn about it.
To associate your repository with the vae-pytorch topic, visit your repo's landing page and select "manage topics."