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ai-surveys

整理AI相关领域的一些综述

awesome-imbalanced-learning

A curated list of awesome imbalanced learning papers, codes, frameworks, and libraries. | 类别不平衡学习：论文、代码、框架与库

awesome-learning-with-label-noise

A curated list of resources for Learning with Noisy Labels

awesome-meta-learning

A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.

awesome-of-long-tailed-recognition

A curated list of long-tailed recognition resources.

c2d

PyTorch implementation of "Contrast to Divide: self-supervised pre-training for learning with noisy labels"

clash_for_windows_pkg

A Windows GUI based on Clash

clashforandroid

A rule-based tunnel for Android.

class-balanced-loss

Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019

class-imbalance

Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.

classifier-balancing

This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 2020

coursera-ml-andrewng-notes

吴恩达老师的机器学习课程个人笔记

deep_learning_with_noisy_labels_literature

This repo consists of collection of papers and repos on the topic of deep learning by noisy labels / label noise.

deeplearning

Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现

dlwpt-code

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

domain

fanqiangssrweb

翻墙网站集锦（科学上网）（加速器）（ssr）（v2ray）（ss）（维基百科）（wikipedia）（谷歌）（YOUTUBE）（奈飞）（Netflix）（原生ip）（专线）（iplc）（内网中转）

file_transport

glc

Gold Loss Correction

handson-unsupervised-learning

Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)

imbalanced-dataset-sampler

A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.

imbalanced-semi-self

[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning

koolshare-clash

:cat: Run Clash Tunnel on Koolshare OpenWrt

labelnoisecorrection

Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction

ldam-drw

[NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss

learning-to-reweight-examples

Code for paper "Learning to Reweight Examples for Robust Deep Learning"

learning-to-reweight-examples-1

PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning

loss-correction

Robust loss functions for deep neural networks (CVPR 2017)

market_manage_system_demo

mesa

NeurIPS’20 | Build powerful ensemble class-imbalanced learning models via meta-knowledge-powered resampler. | 设计元知识驱动的采样器解决类别不平衡问题