7030 Open source projects that are alternatives of or similar to Relativistic Average Gan Keras

Spectral Normalization for Keras Dense and Convolution Layers

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

由淺入深的深度學習資源 Collection of deep learning materials for everyone

A stable algorithm for GAN training

Introduction to generative adversarial networks, with code to accompany the O'Reilly tutorial on GANs

Code for my Master thesis on "Capsule Architecture as a Discriminator in Generative Adversarial Networks".

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

SpecGAN - generate audio with adversarial training

🎎 InfoGAN: Interpretable Representation Learning

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

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

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

Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks

深度学习入门教程, 优秀文章, Deep Learning Tutorial

DCGAN image generator 🖼️.

A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.

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

Generative adversarial networks integrating modules from FUNIT and SPADE for face-swapping.

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

Privacy-preserving generative deep neural networks support clinical data sharing

Projecting images to latent space with StyleGAN2.

Simple Implementation of many GAN models with PyTorch.

On the "steerability" of generative adversarial networks

Tensorflow Implementation of the paper [Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937) (VQ-VAE).

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

PyTorch1.x tutorials, examples and some books I found 【不定期更新】整理的PyTorch 1.x 最新版教程、例子和书籍

Awesome GAN for Medical Imaging

دوره 12 ساعته یادگیری عمیق با چارچوب Keras

Official repository for the paper "High-Resolution Daytime Translation Without Domain Labels" (CVPR2020, Oral)

Invert the color of MNIST images with PyTorch

Synthetic Data Generation for tabular, relational and time series data.

Solve captcha without manually labeling a training set

Generative Adversarial Networks for High Energy Physics extended to a multi-layer calorimeter simulation

Discovering Interpretable GAN Controls [NeurIPS 2020]

Collection of generative models in Pytorch version.

Generative Adversarial Networks in TensorFlow 2.0

Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN

Android TensorFlow MachineLearning MNIST Example (Building Model with TensorFlow for Android)

A Tensorflow implementation of Semi-supervised Learning Generative Adversarial Networks (NIPS 2016: Improved Techniques for Training GANs).

T2F: text to face generation using Deep Learning

A simplified PyTorch implementation of "SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient." (Yu, Lantao, et al.)

TextGAN is a PyTorch framework for Generative Adversarial Networks (GANs) based text generation models.

本仓库将PyTorch官方书籍《Deep learning with PyTorch》（基本摘录版）翻译成中文版并给出可运行的相关代码。

a tensorflow implementation of WGAN

Awesome Generative Adversarial Networks with tensorflow

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

Recurrent (conditional) generative adversarial networks for generating real-valued time series data.

A collection of deep learning tutorials using Tensorflow and Python

Synthesizing and manipulating 2048x1024 images with conditional GANs

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

deeplearning.ai , By Andrew Ng, All video link

深度学习笔记

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

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

Early stopping for 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.

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

📚 [.md & .ipynb] Series of Artificial Intelligence & Deep Learning, including Mathematics Fundamentals, Python Practices, NLP Application, etc. 💫 人工智能与深度学习实战，数理统计篇 | 机器学习篇 | 深度学习篇 | 自然语言处理篇 | 工具实践 Scikit & Tensoflow & PyTorch 篇 | 行业应用 & 课程笔记

머신러닝 입문자 혹은 스터디를 준비하시는 분들에게 도움이 되고자 만든 repository입니다. (This repository is intented for helping whom are interested in machine learning study)

Monk is a low code Deep Learning tool and a unified wrapper for Computer Vision.