Jingxiao-Han

Jingxiao-Han's Stars

• 996icu/996.ICU

  Repo for counting stars and contributing. Press F to pay respect to glorious developers.

  270k4.2k021.2k

• 521xueweihan/HelloGitHub

  :octocat: 分享 GitHub 上有趣、入门级的开源项目。Share interesting, entry-level open source projects on GitHub.

  Language:Python90.5k3k2.7k9.6k

• labmlai/annotated_deep_learning_paper_implementations

  🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

  Language:Python53.9k4461315.6k

• QSCTech/zju-icicles

  浙江大学课程攻略共享计划

  Language:HTML37k1.1k769.4k

• tw93/Pake

  🤱🏻 Turn any webpage into a desktop app with Rust. 🤱🏻 利用 Rust 轻松构建轻量级多端桌面应用

  Language:Rust25.8k1572904.7k

• MSWorkers/support.996.ICU

  Microsoft and GitHub Workers Support 996.ICU

  10.1k126123648

• kxxwz/SJTU-Courses

  上海交通大学课程资料分享

  8.5k329132.1k

• sty945/bank_interview

  :bank: 银行笔试面试经验分享及资料分享（help you pass the bank interview, and get a amazing bank offer!）

  5.1k3610627

• LeiWang1999/FPGA

  帮助大家进行FPGA的入门，分享FPGA相关的优秀文章，优秀项目

  3.8k624656

• Lordog/dive-into-llms

  《动手学大模型Dive into LLMs》系列编程实践教程

  3.2k238282

• weijie-chen/Linear-Algebra-With-Python

  Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assistance of Python computation and visualization.

  Language:Jupyter Notebook2.3k801567

• xinychen/transdim

  Machine learning for transportation data imputation and prediction.

  Language:Jupyter Notebook1.2k3728297

• ken0225/RIS-Codes-Collection

  RIS-Codes-Collection: A Complete Collection contains the Codes for RIS(IRS) Researches.

  1k3515224

• benedekrozemberczki/SimGNN

  A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).

  Language:Python7471147147

• guoshnBJTU/ASTGCN-2019-pytorch

  Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting, AAAI 2019, pytorch version

  Language:Python55560152

• sigmarising/BUPTMasterThesisWord

  The Microsoft Office Word template of BUPT Thesis for Master Degree.

  2153628

• doonny/basic_knowledge

  Things to learn for new students in the Lab for AI chips and systems of BJTU .

  Language:Python1498032

• hisrg/PYNQ_CNN_Accelerator_Tutorial

  中文：

  897124

• txs72/BUPTLinux

  Linux material for students

  Language:Vim Snippet479025

• TiantianUpup/math-learning

  数学学习书籍

  34208

• abdulkarimgizzini/Deep-Learning-Based-Channel-Estimation-Schemes-for-IEEE-802.11p-Standard

  This repository includes the source code of the STA-DNN and TRFI DNN channel estimators proposed in "Deep Learning Based Channel Estimation Schemes for IEEE 802.11 p Standard" and "Joint TRFI and Deep Learning for Vehicular Channel Estimation" papers that are published in the IEEE Access journal and the proceedings of the 2020 IEEE GLOBECOM Workshops, respectively.

  Language:MATLAB32327

• abdulkarimgizzini/Temporal-Averaging-LSTM-based-Channel-Estimation-Scheme-for-IEEE-802.11p-Standard

  This repository includes the source code of the LSTM-based channel estimators proposed in "Temporal Averaging LSTM-based Channel Estimation Scheme for IEEE 802.11 p Standard" paper that is published in the proceedings of the IEEE GLOBECOM 2022 conference that was held in Madrid (Spain).

  Language:MATLAB19116

• JiulongWang/BUPTGranguationPowerPointTemplate

  自制的北邮本科毕设答辩ppt模板

  13100

• LiuDianshi/LiuDianshi.github.io

  My Awesome Blog

  Language:CSS131170

• wzhaha/wireless-sensing-paper

  无线感知相关论文

  Language:Rich Text Format10101

• JingP37/lstm-mlp

  This website provides the simulation code produced by Jing Pan for the following article: Jing Pan, Hangguan Shan, Rongpeng Li, Yinxiao Wu, Weihua Wu, Tony. Q. S. Quek, “Channel estimation based on deep learning in vehicle-to-everything environments,” IEEE Communications Letters, vol. 25, no. 6, pp. 1892-1895, June 2021.

  Language:Python7223

• Dongkesi-2019/Exploring-Zynq-MPSoC-CN

  Exploring Zynq ® MPSoC Chinese

  53

• JonnyS1226/hit-simple-beamer-theme

  源自College-Beamer-Template的哈工大beamer模版（非官方）

  Language:TeX5200

• ky0313JA/My-Paper-of-ISAC

  4101

• Westlibh666/practice

  Language:MATLAB210