Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

For beginner, this will be the best start for VAEs, GANs, and CVAE-GAN. This contains AE, DAE, VAE, GAN, CGAN, DCGAN, WGAN, WGAN-GP, VAE-GAN, CVAE-GAN. All use PyTorch.

Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.

Generation of 128x128 bird images using VAE-GAN with additional feature matching loss

Implementation of "Autoencoding beyond pixels using a learned similarity metric" using Pytorch

Generative models (GAN, VAE, Diffusion Models, Autoregressive Models) implemented with Pytorch, Pytorch_lightning and hydra.

Explore the complete Deep Learning MasterClass in TensorFlow and PyTorch, covering neural networks, GANs, Transformers, VAEs, and more. Your go-to resource for mastering cutting-edge techniques.

VQ-VAE/GAN implementation in pytorch-lightning

PyTorch Lightning Implementation of Diffusion, GAN, VAE, Flow models

[IN PROGRESS] An introduction to generative adversarial networks (GANs) and variational autoencoders (VAEs) in PyTorch, by implementing a few key architectures.

Pytorch implementation of Autoencoding beyond Pixels Using a Learned Similarity Metric

Molecule Generation and Translation Framework. This is a joint PyTorch implementation of three papers in VAE-based molecule generation and translation including JTVAE, V-JTNN-GAN, HierVAE and HierVGNN

A PyTorch implementation of various deep generative models, including Diffusion (DDPM), GAN, cGAN, and VAE.

Collections of generative model(VAE, CVAE, GAN, DCGAN)

implement GANs and VAE using pytorch

The model uses the AE-GAN (Autoencoder Generative Adversarial Network) architecture for generating upsampled images. The model is trained on Celeb-A image (1024 x 1024) dataset where input image is of 128x128 and generated image is of shape 480x480.

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Unoffical pytorch implementation of VAE-GAN

A PyTorch implementation of VAE and GAN for facial image generation.

PyTorch code used in Class-Conditional VAE-GAN for Local-Ancestry Simulation paper

Generativ Models - PixelCNN, GAN, VAE, VQ-VAE in pytorch

VAE & GAN PyTorch Lightning generation of tabular data

A pytorch implementation to 3D-VAE-GAN

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Implementation of GANs and VAEs for image generation and anomaly detection using PyTorch

Includes base format for running various pytorch models (AE, VAE, GANs, Transfer Learning, Custom CNN...)

This is a Machine Learning project. The GAN and VAE network are built and tested using python3 and Pytorch.

This repository contains the implementation of a Variational Autoencoder (VAE) and a Generative Adversarial Network (GAN) using PyTorch for the generation of airfoil shapes. The models are trained on the UIUCAirfoil Coordinates Database, which includes coordinates for nearly 1,600 airfoils.

A curated collection of deep generative model implementations built from scratch using PyTorch. This project aims to explore and compare a wide range of generative modeling techniques including GANs, VAEs, Diffusion Models, and Flows. Each model is implemented with clarity in mind, with visual outputs, loss curves, and detailed documentation

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