#

generative-adversarial-networks

Generative adversarial networks (GAN) are a class of generative machine learning frameworks. A GAN consists of two competing neural networks, often termed the Discriminator network and the Generator network. GANs have been shown to be powerful generative models and are able to successfully generate new data given a large enough training dataset.

Here are 5 public repositories matching this topic...

systemcorp-ai / systemcorp-ai.github.io

SE-MelGAN - Speaker Agnostic Rapid Speech Enhancement

deep-learning generative-adversarial-networks melgan

Updated Jun 11, 2020
HTML

phreakyphoenix / Face-Generation

DCGAN architecture to generate faces from CelebA dataset, made with ❤️ in PyTorch. Do 🌟 the repo if you find it useful.

machine-learning udacity pytorch gan dcgan dlnd udacity-nanodegree generative-adversarial-networks udacity-deep-learning face-generation dlnd-face-generation pytorch-gan udacity-project deep-learning-nanodegree dcgan-pytorch create-faces

Updated May 29, 2020
HTML

heschmat / deep-learning-projects

Projects for Udacity Deep Learning Nanodegree Program: CNN, RNN, GANs

deep-learning sentiment-analysis cnn pytorch recurrent-neural-networks healthcare gan rnn convolutional-neural-networks generative-adversarial-networks medical-image-processing

Updated May 8, 2021
HTML

ragamarkely / face_generation_dcgan

Build a Deep Convolutional Generative Adversarial Networks (DCGANs) to generate new images of faces.

gans generative-adversarial-networks dcgans deep-convolutional-neural-networks

Updated Apr 16, 2018
HTML

kritisharma23 / face-generation

Generate Face Images using Generative Adversarial Networks (GAN) - Pytorch

deep-learning pytorch generative-adversarial-networks

Updated Sep 24, 2020
HTML

Released June 10, 2014

Followers: 248 followers
Wikipedia: Wikipedia

Related Topics

deep-learning neural-network