greysakura

drawio-desktop

Official electron build of draw.io

wenyan

文言文編程語言 A programming language for the ancient Chinese.

nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

transferlearning

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

cleanlab

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Flux.jl

Relax! Flux is the ML library that doesn't make you tensor

dockerpi

A Virtualised Raspberry Pi inside a Docker image

pytorch-distributed

A quickstart and benchmark for pytorch distributed training.

Mocha.jl

Deep Learning framework for Julia

Efficient-Computing

Efficient computing methods developed by Huawei Noah's Ark Lab

CloserLookFewShot

source code to ICLR'19, 'A Closer Look at Few-shot Classification'

awesome-papers-fewshot

Collection for Few-shot Learning

qgis-earthengine-examples

A collection of 300+ Python examples for using Google Earth Engine in QGIS

ai_projects

AI projects

lstm-crf-pytorch

LSTM-CRF in PyTorch

RSNA2019_Intracranial-Hemorrhage-Detection

Code for 1st Place Solution in Intracranial Hemorrhage Detection Challenge @ RSNA2019

CDAN

Code release for "Conditional Adversarial Domain Adaptation" (NIPS 2018)

Recursive-Cascaded-Networks

[ICCV 2019] Recursive Cascaded Networks for Unsupervised Medical Image Registration

MLBox

Machine Learning Algorithms implementations

train_arch

cnn+rnn+attention: vgg(vgg16,vgg19)+rnn(LSTM, GRU)+attention, resnet(resnet_v2_50,resnet_v2_101,resnet_v2_152)+rnnrnn(LSTM, GRU)+attention, inception_v4+rnn(LSTM, GRU)+attention, inception_resnet_v2+rnn(LSTM, GRU)+attention,..... vgg(vgg16,vgg19), resnet(resnet_v2_50,resnet_v2_101,resnet_v2_152), inception_v4, inception_resnet_v2,.....

nova

NOVA is a tool for annotating and analyzing behaviours in social interactions. It supports Annotators using Machine Learning already during the coding process. Further it features both, discrete labels and continuous scores and a visuzalization of streams recorded with the SSI Framework.

MADAN

Pytorch Code release for our NeurIPS paper "Multi-source Domain Adaptation for Semantic Segmentation"

NasUnet

DAL

Domain agnostic learning with disentangled representations

BF3S

Boosting Few-Shot Visual Learning with Self-Supervision

JuliaBLAS.jl

coteaching_plus

ICML'19 How does Disagreement Help Generalization against Label Corruption?

USSS_ICCV19

Code for Universal Semi-Supervised Semantic Segmentation models paper accepted in ICCV 2019

FocalLoss

Weighted Focal Loss for multilabel classification

pdf2eps

Convert PDF to encapsulated PostScript