Shi Yukun's repositories
weixin-java-tools
全能微信Java开发工具包，支持包括微信支付、开放平台、小程序、企业号和公众号等的开发
AE-GAN
AE-GAN
APIJSONAuto
自动化接口管理工具，自动生成代码、自动静态检查、自动化回归测试、自动生成文档与注释等。
bkd_fedgnn
Implementation of paper "More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks"
Community-Detection-MTFL
🔬 本项目为SWPU2022届本科毕业设计《基于社区检测的多任务聚类联邦学习》。本研究提出了一种多任务聚类联邦学习的新方法，该方法的特点是基于社区检测来进行聚类簇的动态划分。
Computer_Graphics
华中科技大学《计算机图形学》MOOC课程实验 ——万琳老师
CTGAN
Conditional GAN for generating synthetic tabular data.
easyFL
An experimental platform to quickly realize and compare with popular centralized federated learning algorithms. A realization of federated learning algorithm on fairness (FedFV, Federated Learning with Fair Averaging, https://fanxlxmu.github.io/publication/ijcai2021/) was accepted by IJCAI-21 (https://www.ijcai.org/proceedings/2021/223).
EasyFL-1
An easy-to-use federated learning platform
federated-learning
A PyTorch Implementation of Federated Learning http://doi.org/10.5281/zenodo.4321561
FedGS
FedGS: Federated Graph-based Sampling with Arbitrary Client Availability, arxiv.org/abs/2211.13975) was accepted by AAAI 2023 Conference.
FedLab
A flexible Federated Learning Framework based on PyTorch, simplifying your Federated Learning research.
FedLab-benchmarks
Standard federated learning implementations in FedLab and FL benchmarks.
FedPerGNN
code of FedGNN
FEDXGBOOST-MPI4PY
Secured Federated Learning XGBoost - This project provides the implementation of FL XGBoost in python, which allows the fast prototyping of scecured protocols.
kfed
KFedExps -> kfed
Labs-Federated-Learning
Accenture Labs Federated Learning
MP-FedXGB
An Efficient Learning Framework For Federated XGBoostUsing Secret Sharing And Distributed Optimization
PDMINet
Prototype-Driven and Multi-Expert Integrated Multi-Modal MR Brain Tumor Image Segmentation
PFL-Non-IID
Personalized federated learning simulation platform with non-IID and unbalanced dataset
ProtoKD
[ICASSP 2023] Prototype Knowledge Distillation for Medical Segmentation with Missing Modality
REKCARC-TSC-UHT
清华大学计算机系课程攻略 Guidance for courses in Department of Computer Science and Technology, Tsinghua University
secure-kmean-clustering
Practical Privacy-Preserving K-means Clustering (PETS-2020)