A resource for learning about Machine learning & Deep Learning
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Updated
Feb 9, 2024 - Python
A resource for learning about Machine learning & Deep Learning
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!
Simple Implementation of many GAN models with PyTorch.
A modern PyTorch implementation of SRGAN
[ECCV 2020] Official Pytorch implementation for "Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification". SOTA results for ZSL and GZSL
PyTorch Tutorial for beginners
Implement Human Pose Transfer papers with Pytorch
PyTorch implementation of Deterministic Generative Adversarial Imitation Learning (GAIL) for Off Policy learning
Noise2Void - Learning Denoising from Single Noisy Images
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Tutorial for machine learning with python
Person re-identification, a tool used in intelligent video surveillance, is the task of correctly identifying individuals across multiple images captured under varied scenarios from multiple cameras. Solving this problem is inherently a challenging one because of the issues posed to it by low resolution images, illumination changes per image, un…
Pytorch implementation of a Conditional WGAN with Gradient Penalty
Non-official + minimal reimplementation of HoloGAN by Nguyen-Phuoc, et al: https://arxiv.org/abs/1904.01326
Image-to-Image Translation with Conditional Adversarial Networks
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
PANDA (Pytorch) pipeline, is a computational toolbox (MATLAB + pytorch) for generating PET navigators using Generative Adversarial networks.
Enhanced Super-Resolution Generative Adversarial Networks
[CNN PROGRAMMING] 005 - DCGAN
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