Taicheng Huang's starred repositories
dlwpt-code
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
BrainSpace
BrainSpace is an open-access toolbox that allows for the identification and analysis of gradients from neuroimaging and connectomics datasets | available in both Python and Matlab |
pytorch-pretrained-BigGAN
🦋A PyTorch implementation of BigGAN with pretrained weights and conversion scripts.
torch-lrcn
An implementation of the LRCN in Torch
two-stream-pytorch
PyTorch implementation of two-stream networks for video action recognition
flownet2-pytorch
Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
word_cloud
A little word cloud generator in Python
two-stream-action-recognition
Using two stream architecture to implement a classic action recognition method on UCF101 dataset
Action_Recognition_Zoo
Codes for popular action recognition models, verified on the something-something data set.
ColeAnticevicNetPartition
Public release of The Cole-Anticevic Brain-wide Network Partition (CAB-NP)
pytorch-handbook
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
deeplearning-models
A collection of various deep learning architectures, models, and tips
pytorch-book
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》)
TensorFlow-Course
:satellite: Simple and ready-to-use tutorials for TensorFlow
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Skill-Tree
🐼 准备秋招,欢迎来树上取果实
multiBrain
A list of brain imaging datasets with multiple scans per subject. Feel free to update the list via 'pull requests'!
tutorial-prni-2017
This repository contains iPython notebooks that run on the octave kernel to accompany tutorial and slides presented at PRNI
simplified-deeplearning
Simplified implementations of deep learning related works
hypertools
A Python toolbox for gaining geometric insights into high-dimensional data