Showing 41-60 of 130 projects
A PyTorch library for computing Fréchet Inception Distance (FID), a metric used to evaluate generative adversarial networks.
A curated list of papers on Generative Adversarial Networks (GANs), a powerful class of deep learning models.
A collection of articles on machine learning concepts and techniques by the author
A comprehensive collection of deep learning resources including courses, case studies, and interview questions.
Generative Adversarial Networks (GANs) library for PyTorch, enabling image generation and conditional/unconditional image synthesis.
A photo-realistic single image super-resolution using a generative adversarial network (SRGAN) library.
Generates synthetic tabular data for machine learning and AI applications
A denoising autoencoder with adversarial losses and attention mechanisms for face swapping.
Create Anime Characters with AI-powered tools
A GAN-based face editing tool that allows users to edit faces using sketches and color inputs.
Official PyTorch implementation of the SinGAN paper, a generative model that can be trained on a single natural image.
A PyTorch implementation of the Wasserstein GAN (WGAN) algorithm for generative adversarial networks.
A tutorial repository for learning deep learning with PyTorch, covering topics like CNNs, GANs, and RNNs.
This repository provides resources and implementations of Generative Adversarial Nets, a powerful machine learning technique.
This repository provides a roadmap and code samples for machine learning, deep learning, and related AI technologies.
This is an unofficial PyTorch implementation of the BigGAN deep generative adversarial network (GAN) model.
A JavaScript playground for generating images from text prompts using Stable Diffusion AI technology.
A generative adversarial network (GAN) model for learning and transferring Chinese character styles.
MUNIT is a deep learning-based method for multimodal unsupervised image-to-image translation, enabling vibe coders to create diverse and stylized images.
Implementation of papers in 100 lines of code
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