generative-models
Generative models
Annotated implementations of various deep generative models using PyTorch
Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
498 stars
16 watching
75 forks
Language: Jupyter Notebook
last commit: over 6 years ago autoencoderbegandiscriminatordraganfganfishergangangenerative-adversarial-networkgenerative-modelsinfoganlsganmachine-learningmmgannsganpythonpytorchraganvaewassersteinwgan
Related projects:
Repository | Description | Stars |
---|---|---|
| A PyTorch implementation of a Generative Adversarial Network (GAN) for discovering cross-domain relations. | 1,084 |
| Implementation of a deep learning model for generating high-quality images with improved stability and variation. | 538 |
| An implementation of Generative Adversarial Networks in PyTorch for generating realistic data from a given distribution. | 32 |
| A PyTorch implementation of a Generative Query Network model for generating 3D scenes and rendering them in various styles. | 322 |
| This project aims to develop a generative model for 3D multi-object scenes using a novel network architecture inspired by auto-encoding and generative adversarial networks. | 103 |
| A PyTorch implementation of Generative Adversarial Networks for anime face drawing | 1,282 |
| A collection of software frameworks and implementations for training generative models using GANs, VAEs, RBMs, and other techniques. | 7,351 |
| An implementation of DeepMind's Relational Recurrent Neural Networks (Santoro et al. 2018) in PyTorch for word language modeling | 245 |
| Converts PyTorch models to Keras models | 859 |
| Trains a large-scale PyTorch language model on the 1-Billion Word dataset | 123 |
| A collection of generative models implemented in Python using PyTorch | 54 |
| A PyTorch implementation of an image-to-image translation model that generates new images from paired training data. | 1,491 |
| A Python framework for building deep learning models with optimized encoding layers and batch normalization. | 2,044 |
| Reproducible PyTorch inference of the Progressive Growing of GANs model using CelebA training snapshot | 322 |
| An implementation of a lightweight convolutional neural network architecture for mobile devices | 191 |