Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch

Python package with source code from the course "Creative Applications of Deep Learning w/ TensorFlow"

Official implementation of CVPR2020 paper "Learning to Dress 3D People in Generative Clothing" https://arxiv.org/abs/1907.13615

Stochastic Adversarial Video Prediction

All NLP you Need Here. 目前包含15个NLP demo的pytorch实现（大量代码借鉴于其他开源项目，原先是自己玩的，后来干脆也开源出来）

Tensorflow code of "autoencoding beyond pixels using a learned similarity metric"

dcgan combined with vae in pytorch!

Implementations of various Deep Learning models in PyTorch and TensorFlow.

Code and notebooks related to the paper: "Reconstructing Faces from fMRI Patterns using Deep Generative Neural Networks" by VanRullen & Reddy, 2019

A VAE-GAN model designed for learning 3d shape from a single 2d image. Trained on ShapeNetCore Dataset

Hybrid Architecture Network, originally VAE+CPPN+GAN by hardmaru

Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to hide data inside images

Simple Tensorflow implementation of the paper Autoencoding Beyond Pixels Using a Similarity Metric

Repository of all notebooks used in the GANs and VAEs event.

Implementation of https://arxiv.org/pdf/1805.12352.pdf (ICLR 2019)

本项目实现了一种基于 VAE-CycleGAN 的图像重建无监督缺陷检测算法。该算法结合了变分自编码器 (VAE) 和 CycleGAN 的优势，无需标注数据即可检测图像中的缺陷/异常。This project implements an unsupervised defect detection algorithm for image reconstruction based on VAE-CycleGAN. This algorithm combines the advantages of variational autoencoders (VAE) and CycleGAN to detect defects in images without any supervision.

Official implementation of Action-Conditioned Frame Prediction Without Discriminator

cVAE, VQ-VAE, VQ-VAE2, cVAE-cGAN, PixelCNN and Gated PixelCNN in tensorflow 2.x and keras

A tensorflow implementation of VAE-GAN. This is the first approach which viewed the discriminator as a loss function to improve.