591 Open source projects that are alternatives of or similar to Deep Generative Models

An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU) in ICLR 2017.

Focal Frequency Loss for Generative Models

Example projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.

Tensorflow implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Netwokrs for MNIST dataset.

Learning about Haskell with Variational Autoencoders

Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST

The implementation of Relativistic average GAN with Keras

Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano

No description or website provided.

An implementation of VAEGAN (variational autoencoder + generative adversarial network).

rectorch is a pytorch-based framework for state-of-the-art top-N recommendation

Collection of generative models in Tensorflow

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

Collection of generative models in Pytorch version.

A curated list of dedicated resources and applications

Timbre transfer with variational autoencoding and cycle-consistent adversarial networks. Able to transfer the timbre of an audio source to that of another.

Tensorflow implementation of conditional variational auto-encoder for MNIST

Tensorflow implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Adversarial Networks (cDCGAN) for MANIST dataset.

Pytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets

Interactive exploration of MNIST variational autoencoder latent space with React and tensorflow.js.

Assessing Generative Models via Precision and Recall (official repository)

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

Generative Adversarial Networks in TensorFlow 2.0

Generative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Important Generative Model Papers, Courses, etc..

Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset

TextBox is an open-source library for building text generation system.

Experiments for understanding disentanglement in VAE latent representations

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.

Invert the color of MNIST images with PyTorch

If you've always wanted to learn about deep-learning but don't know where to start, then you might have stumbled upon the right place!

Stochastic Adversarial Video Prediction

A Pytorch implementation of "Deep Convolutional Generative Adversarial Networks"

🎎 InfoGAN: Interpretable Representation Learning

Lagrangian VAE

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

Tensorflow implementation of variational auto-encoder for MNIST

Generating Videos with Scene Dynamics. NIPS 2016.

Given an image and a target viewpoint, generate synthetic image in the target viewpoint

A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

This is just a collection of projects that made during my DEEPLEARNING NANODEGREE by UDACITY

ICML 2019. Turn a pre-trained GAN model into a content-addressable model without retraining.

Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)

🔥🔥 PyTorch implementation of "Progressive growing of GANs (PGGAN)" 🔥🔥

Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN

🦓<->🦒 🌃<->🌆 A collection of image to image papers with code (constantly updating)

Reproduction code for WGAN-LP

Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)

Early stopping for PyTorch

Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model.

An AI for Music Generation

PyTorch implementation of various methods for continual learning (XdG, EWC, online EWC, SI, LwF, GR, GR+distill, RtF, ER, A-GEM, iCaRL).

Generate your own cartoon-style images with CartoonGAN (CVPR 2018), powered by TensorFlow 2.0 Alpha.

Dataset and Code for our CVPR'18 paper ST-CGAN: "Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal"

List of useful data augmentation resources. You will find here some not common techniques, libraries, links to github repos, papers and others.

Synthesizing and manipulating 2048x1024 images with conditional GANs

Awesome Generative Adversarial Networks with tensorflow