Collection of RNN GAN SNN CNN in Tensorflow
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Updated
Jun 2, 2024 - Jupyter Notebook
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.
Collection of RNN GAN SNN CNN in Tensorflow
The collection of pre-trained, state-of-the-art AI models for ailia SDK
Pytorch implementation of AnimeGAN for fast photo animation
Just some notebooks I wrote to research some fun stuff in hobby time
A Great Collection of Deep Learning Tutorials and Repositories
《李宏毅深度学习教程》(李宏毅老师推荐👍),PDF下载地址:https://github.com/datawhalechina/leedl-tutorial/releases
Generate Art
This repository contains an implementation of a Deep Convolutional Generative Adversarial Network (DCGAN) trained on the FashionMNIST dataset. The project aims to generate realistic images of clothing items using a GAN architecture. It includes model definitions, training scripts, and visualizations of generated images at various training stages.
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List of protein (enzymes and PPIs) conformations and molecular dynamics using generative artificial intelligence and deep learning
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HyMPS will be a platform-indipendent software suite for advanced audio/video contents production.
Welcome to the repository dedicated to exploring Generative Artificial Intelligence (AI) techniques in Computer Vision. This repository serves as a centralized hub for various projects, research, and resources related to generating visual content using AI models.
New flexible and efficient image generation framework that sets new SOTA on FFHQ-256 with FID 2.05, 2022
Thesis "Development of domain adaptation methods for generative models"
Simple interface to synthesize complex and highly dimensional datasets using Gretel APIs.
Released June 10, 2014