Gans Specialization course by deeplearning.ai: solved assignments and labs
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Updated
May 6, 2024 - Jupyter Notebook
Gans Specialization course by deeplearning.ai: solved assignments and labs
A resource for learning about Machine learning & Deep Learning
This repo implements a simple GAN with fc layers and trains it on MNIST
A scratch GAN to generate images of mixed world coins using PyTorch
An Android App where the user can generate a grid of sticker image, and the user can also save that image for further uses. In the backend gan model is used to generate new Images and by using rest API those images bring to android app.
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.
Simple Implementation of many GAN models with PyTorch.
Simple generative adversarial network implementation using pytorch on MNIST dataset.
A class-based styling approach for Real-Time Domain Adaptation in Semantic Segmentation applied within the realm of autonomous driving solutions. Final project from MLDL course 2020/2021
Implementation of the paper "Generative Adversarial Networks — Goodfellow et al. (2014)" in Pytorch
Trying to learn PyTorch
PyTorch 官方中文教程包含 60 分钟快速入门教程,强化教程,计算机视觉,自然语言处理,生成对抗网络,强化学习。欢迎 Star,Fork!
PyTorch Bootcamp
Noise2Void - Learning Denoising from Single Noisy Images
A collection of small-scale projects that helped me learn the basics of the PyTorch framework
[ECCV 2020] Official Pytorch implementation for "Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification". SOTA results for ZSL and GZSL
PyTorch implementation of various GAN architectures.
A web-app based on Wasserstein Generative Adversarial Network architecture with GP that generates multiple realistic paintings, trained on 8k Albrecht Dürer's paintings, includes super-res mode.
This repository contains all the work I have done during the course Deep Learning with PyTorch : Zero to GANs under Jovian.ai.
PANDA (Pytorch) pipeline, is a computational toolbox (MATLAB + pytorch) for generating PET navigators using Generative Adversarial networks.
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