Python & JAVA Solutions for Leetcode

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Techniques for deep learning with satellite & aerial imagery

Retrieval of Multiple Environmental Parameters from Images with Deep Learning

Code for the paper "MSMatch: Semi-Supervised Multispectral Scene Classification with Few Labels"

📡 PyTorch Lightning Implementations of Recent Satellite Image Classification !

KDD 2023 accepted paper, FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy

Come join the best place on the internet to learn AI skills. Use code "aicodetranslator" for an extra 20% off.

ICML2022: Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning

《Python编程：从入门到实践》- python3.5

Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

Convert Machine Learning Code Between Frameworks

FedScale is a scalable and extensible open-source federated learning (FL) platform.

An implementation for "Federated Learning with Non-IID Data via Local Drift Decoupling and Correction"

37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 20 datasets.

An easy-to-use federated learning platform

An easy-to-use federated learning platform

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

Source code for the paper "FedLess: Secure and Scalable Federated Learning Using Serverless Computing" (IEEE BigData 2021)

Federated Learning Simulator (FLSim) is a flexible, standalone core library that simulates FL settings with a minimal, easy-to-use API. FLSim is domain-agnostic and accommodates many use cases such…

Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data

Federated Multi-Task Learning

Scripts for figures and calculations of the manuscript by Warnat-Herresthal el al. 2020

やり直すんだ。そして、次はうまくやる。

Official code implementation for "Personalized Federated Learning using Hypernetworks" [ICML 2021]

Code for Personalized Federated Learning with Gaussian Processes

Experiments code for the paper "Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques"