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junchenhe's Projects

bert icon bert

TensorFlow code and pre-trained models for BERT

citeulike-t icon citeulike-t

Dataset citeulike-t for 'Collaborative Topic Regression with Social Regularization' (CTRSR)

convcnp icon convcnp

Implementation of the Convolutional Conditional Neural Process

cs-books icon cs-books

🔥🔥超过1000本的计算机经典书籍、个人笔记资料以及本人在各平台发表文章中所涉及的资源等。书籍资源包括C/C++、Java、Python、Go语言、数据结构与算法、操作系统、后端架构、计算机系统知识、数据库、计算机网络、设计模式、前端、汇编以及校招社招各种面经~

cskaoyan icon cskaoyan

提供计算机考研和软件工程考研专业的各个学校 考研真题

csqa_implementation icon csqa_implementation

This repository contains an implementation for the Complex Sequential Question Answering (CSQA) (Saha et al. 2018) task.

dgl_chinese_manual icon dgl_chinese_manual

This is the Chinese manual of the graph neural network library DGL, currently contains the User Guide.

dive-into-dl-pytorch icon dive-into-dl-pytorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

docker_practice icon docker_practice

Learn and understand Docker technologies, with real DevOps practice!

gan_theories icon gan_theories

Resources and Implementations of Generative Adversarial Nets which are focusing on how to stabilize training process and generate high quality images: DCGAN, WGAN, EBGAN, BEGAN, etc.

gat icon gat

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

gnnpapers icon gnnpapers

Must-read papers on graph neural networks (GNN)

hyper-sagnn icon hyper-sagnn

hypergraph representation learning, graph neural network

java icon java

存放JAVA开发的设计**、算法:《剑指Offer》、《编程珠玑》、《深入理解Java虚拟机:JVM高级特性与最佳实践》、《重构-改善既有代码的设计 中文版》、《clean_code(中文完整版)》、《Java编程**(第4版)》、《Java核心技术 卷I (第8版)》、《Quartz_Job+Scheduling_Framework》;一些大的上传不上来的文件在README

java-1 icon java-1

一些用Java写的小东西(没什么用,大家不要star了😄)

kanaquiz icon kanaquiz

Hiragana/Katakana Speed Reading Quiz in Command Line !! :sunglasses:

learn-vim icon learn-vim

Vim 实操教程(Learning Vim)Vim practical tutorial.

librxe-dev icon librxe-dev

Development repository for RXE user space code.

lihang icon lihang

Statistical learning methods, 统计学习方法 [李航] 值得反复读. [笔记, 代码, notebook, 参考文献, Errata, lihang]

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