federated-learning

A curated list of references for MLOps

Perform data science on data that remains in someone else's server

Flower: A Friendly Federated AI Framework

An Industrial Grade Federated Learning Framework

FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.

A unified framework for privacy-preserving data analysis and machine learning

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

FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai

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

A framework for fine-tuning retrieval-augmented generation (RAG) systems.

A multi-agent research laboratory for data distillation and long evolutionary collaborative reasoning.

I put all my exploration around AI in reproducible notebooks in this repository

NAACL '24 (Best Demo Paper RunnerUp) / MlSys @ NeurIPS '23 - RedCoast: A Lightweight Tool to Automate Distributed Training and Inference

CVPR 2024 accepted paper, An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning

🔥 Tuning LLMs with 15+ Federated Fine-tuning Methods

[AAAI'25] The implementation of paper "Federated Foundation Models on Heterogeneous Time Series" | The first work to explore time series foundation models on federated setting.

Library for Federated Emergence & Foundation Models