48 Open source projects that are alternatives of or similar to FedDA

A library for answering questions using data you cannot see

A curated list of references for MLOps

An Industrial Grade Federated Learning Framework

电力人工智能数据竞赛——液压吊车目标检测赛道

The repo for the FeTS Challenge

Federated gradient boosted decision tree learning

Federated Learning based Deep Learning. Docs: https://fets-ai.github.io/Front-End/

Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond

A scalable, high-performance serving system for federated learning models

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).

Federated Learning mini-framework with Keras

The origin of the Non-IID phenomenon is the personalization of users, who generate the Non-IID data. With Non-IID (Not Independent and Identically Distributed) issues existing in the federated learning setting, a myriad of approaches has been proposed to crack this hard nut. In contrast, the personalized federated learning may take the advantage…

Standard federated learning implementations in FedLab and FL benchmarks.

Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct your research on backdoors.

Here is the official implementation of the model KD3A in paper "KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation".

Model-Contrastive Federated Learning (CVPR 2021)

Implementation of Federated Learning to Person Re-identification (Code for ACMMM 2020 paper)

Federated posterior averaging implemented in JAX

Substra is a framework for traceable ML orchestration on decentralized sensitive data.

Personalized Federated Learning with Moreau Envelopes (pFedMe) using Pytorch (NeurIPS 2020)

FedGroup, A Clustered Federated Learning framework based on Tensorflow

Full stack service enabling decentralized machine learning on private data

Official code for "Throughput-Optimal Topology Design for Cross-Silo Federated Learning" (NeurIPS'20)

Proof of Concept of a Federated Learning framework that maintains the privacy of the participants involved.

SRDS 2020: End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things

Healthcare-Researcher-Connector Package: Federated Learning tool for bridging the gap between Healthcare providers and researchers

Privacy Preserving Vertical Federated Learning

Paper collection of federated learning. Conferences and Journals Collection for Federated Learning from 2019 to 2021, Accepted Papers, Hot topics and good research groups. Paper summary

Simulate collaborative ML scenarios, experiment multi-partner learning approaches and measure respective contributions of different datasets to model performance.

Federated Learning on HyperLedger Aries

The core runtime engine for Ambianic Edge devices.

FedNLP: An Industry and Research Integrated Platform for Federated Learning in Natural Language Processing, Backed by FedML, Inc. The Previous Research Version is Accepted to NAACL 2022

tf implementation of federated learning

DBA: Distributed Backdoor Attacks against Federated Learning (ICLR 2020)

Federated Principal Component Analysis Revisited!

电力人工智能数据竞赛——安全帽未佩戴行为目标检测赛道基准模型

FEDL-Federated Learning algorithm using TensorFlow (Transaction on Networking 2021)

This is the code for Addressing Class Imbalance in Federated Learning (AAAI-2021).

Bachelor's Thesis in Computer Science: Privacy-Preserving Federated Learning Applied to Decentralized Data

CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)

The implementation of "Towards Faster and Better Federated Learning: A Feature Fusion Approach" (ICIP 2019)

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

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

Federated Learning on Non-IID Data Silos: An Experimental Study (ICDE 2022)

FedDANE: A Federated Newton-Type Method (Asilomar Conference on Signals, Systems, and Computers ‘19)

Proof Of Concept of DEcentralised Machine Learning on top of the Golem (https://golem.network/) architecture

Codes for AAAI 2019 DeepSTN+: Context-aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis

TianChi AIEarth Contest Solution