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University of Miami
Stars
A Multiphase flow simulation platform using Direct-forced Immersed Boundary Method based on Spectral element solver Nek5000.
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch:入门与实战》)
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Keras implementation of class activation mapping
An implementation of Grad-CAM with keras
pytorch handbook是一本开源的书籍,目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门,其中包含的Pytorch教程全部通过测试保证可以成功运行
A list of papers relating Computational Physics and Machine Learning
A PyTorch implementation of "Multimodal Generative Models for Scalable Weakly-Supervised Learning" (https://arxiv.org/abs/1802.05335)
AttGAN PyTorch Arbitrary Facial Attribute Editing: Only Change What You Want
Chronicles of brilliant deep learning ideas
The code of the paper 'Learning-Residual-Images-for-Face-Attribute-Manipulation' is implemented by TensorFlow
zjost / InfoGAN
Forked from openai/InfoGANCode for reproducing key results in the paper "InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets"
Code for reproducing experiments in "SCGAN: Disentangled Representation Learning by Adding Similarity Constraint on Generative Adversarial Nets"
Learning interpretable dimensions for conceptual spaces using deep representation learning.
Implementation of Visual Feature Attribution using Wasserstein GANs (VAGANs, https://arxiv.org/abs/1711.08998) in PyTorch
Resources and Implementations of Generative Adversarial Nets: GAN, DCGAN, WGAN, CGAN, InfoGAN
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
PyTorch implementations of Generative Adversarial Networks.
SaGAN PyTorch "Generative Adversarial Network with Spatial Attention for Face Attribute Editing"
Keras implementations of Generative Adversarial Networks.
Tensorflow implementation of 'Visual Feature Attribution using Wasserstein GANs'
Demo code for Attention-Aware Generative Adversarial Networks paper
The code for the machine learning (Coursera) class by Andrew Ng from Stanford University
Analysis satellite images of typhoons in deep-learning (CNN).
Hurricane Track Visualization in Python
Web site for www.py4e.com and source to the Python 3.0 textbook