dp-cgans
A library to generate synthetic tabular or RDF data using Conditional Generative Adversary Networks (GANs) combined with Differential Privacy techniques.
dgmr
Implementation of DeepMind's Deep Generative Model of Radar (DGMR) https://arxiv.org/abs/2104.00954
https://github.com/ydataai/ydata-synthetic
Synthetic data generators for tabular and time-series data
https://github.com/bchao1/fun-with-mnist
Playing with MNIST. Machine Learning. Generative Models.
https://github.com/csinva/gan-vae-pretrained-pytorch
Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
t81_558_deep_learning
T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis
https://github.com/csinva/matching-with-gans
Matching in GAN latent space for better bias benchmarking and semantic image editing. 👶🏻🧒🏾👩🏼🦰👱🏽♂️👴🏾
https://github.com/bchao1/conditional-gan-anime-generation
Conditional anime generation using conditional GAN.
https://github.com/blutjens/eie-earth-public
Official repo for 'Generating Physically-Consistent Satellite Imagery for Climate Visualizations'
https://github.com/ai-forever/movqgan
MoVQGAN - model for the image encoding and reconstruction
https://github.com/chenliu-1996/gan-evaluator
A pip-installable evaluator for GANs (IS and FID). Accepts either dataloaders or individual batches. Supports on-the-fly evaluation during training. A working DCGAN SVHN demo script provided.
https://github.com/cedrickchee/gandissect
PyTorch-based tools for visualizing and understanding the neurons of a GAN.
https://github.com/christophreich1996/semantic_pyramid_for_image_generation
PyTorch reimplementation of the paper: "Semantic Pyramid for Image Generation" [CVPR 2020].
ganslate
Simple and extensible GAN image-to-image translation framework. Supports natural and medical images.
argan
[Open Source]. ARGAN - The improved version of AnimeGAN. Landscape photos/videos to anime
wsg-gan-color-edition
Weak Segmentation-Guided GAN for Realistic Color Edition presented at ICIAP 2023
mmgeneration
MMGeneration is a powerful toolkit for generative models, based on PyTorch and MMCV.
https://github.com/abdulmanaf12/pediatric-chest-pneumonia-classification
This project is all about interpreting Chest X-ray images, and the task is to classify whether X-ray image got infected by Pneumonia or not. we also used here GAN and various type of augmentation techniques.
https://github.com/chychen/basketballgan
Basketball coaches often sketch plays on a whiteboard to help players get the ball through the net. A new AI model predicts how opponents would respond to these tactics.
gan-uncertainty
Hybrid workflow with two main steps: (a) creating a dataset of training images using GANs; (b) building geostatistical models using the synthetic TI and the existing conditional data.
awesome-data-synthesis
A curated list of awesome resources for creating synthetic data
diffgan-tts
PyTorch Implementation of DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANs
paganini
A generative adversarial network trained to compose virtuosic classical music with an SVM discriminator system (C-RNN-GAN).
https://github.com/christophreich1996/multi-stylegan
Official and maintained implementation of the paper "Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy" [MICCAI 2021].
https://github.com/bchao1/dcgan-random-anime-generation
Anime generation using vanilla GAN, WGAN, and LSGAN.
p3forecast
a Personalized Privacy Preserving cloud workload prediction framework based on Federated Generative Adversarial Networks (GANs), which allows cloud providers with Non-IID workload data to collaboratively train workload prediction models as preferred while protecting privacy.
https://github.com/cedrickchee/relativisticgan
Code for replication of the paper "The relativistic discriminator: a key element missing from standard GAN"
approaching-an-unknown-communication-system
Code/supplement for the paper "Approaching an unknown communication system by latent space exploration and causal inference"
ganonymization
A GAN-based Face Anonymization Framework for Preserving Emotional Expressions
multiscale-adversarial-attention-gates
Code for the paper: Valvano G. et al. (2021), Learning to Segment from Scribbles using Multi-scale Adversarial Attention Gates