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Yiyang's Projects

interview icon interview

2021秋招 计算机视觉算法岗面经整理——包含实习和校招等 内推整理

interview-questions icon interview-questions

机器学习/深度学习/Python/Go语言面试题笔试题(Machine learning Deep Learning Python and Golang Interview Questions)

involution icon involution

[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator

ipython icon ipython

Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.

ivd-net icon ivd-net

Repository containing the source code of the IVD-Net segmentation network that we proposed for the MICCAI 2018 IVD segmentation challenge.

machine-learning-learning-notes icon machine-learning-learning-notes

周志华《机器学习》又称西瓜书是一本较为全面的书籍,书中详细介绍了机器学习领域不同类型的算法(例如:监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等),记录了本人在学习过程中的理解思路与扩展知识点,希望对新人阅读西瓜书有所帮助!

malware_analysis icon malware_analysis

Classification of infected and benign files using PE header file analysis.

mesa icon 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

minibase icon minibase

CS560 - A mini-database system implementation with features like HeapFiles, B-Trees, Sort-Merge Joins, BufferManager.

miningzhidaoqacorpus icon miningzhidaoqacorpus

ZhiDaoChatCorpus, zhidao QA pairs crawled from Baidu zhidao which contains more than 5,800,000 question and 9,830,000 answers with certain tags。百度知道问答语料库,包括超过580万的问题,938万的答案,5800个分类标签。基于该问答语料库,可支持多种应用,如闲聊问答,逻辑挖掘。

ml-nlp icon ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。

musdac icon musdac

Multi-Space Domain Adaptive Classification

nnpu_tf icon nnpu_tf

Code for reproducing experiments on MNIST and CIFAR-10 in paper "Positive-Unlabeled Learning with Non-Negative Risk Estimator".

nnpusb icon nnpusb

Learning from positive and unlabeled data with a selection bias (nnPUSB) reproductive code on MNIST and CIFAR10

nrgnn icon nrgnn

A PyTorch implementation of "NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs" (KDD 2021)

openbg-csk icon openbg-csk

Baselines for CCKS 2022 Task "Commonsense Knowledge Salience Evaluation"

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