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Type: Organization
Type: Organization
This is the code for Addressing Class Imbalance in Federated Learning (AAAI-2021).
🧑🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Automated deep learning algorithms implemented in PyTorch.
Avalanche: an End-to-End Library for Continual Learning based on PyTorch.
Federated learning on graph and tabular data related papers, frameworks, and datasets.
The implementation of various lightweight networks by using PyTorch. such as:MobileNetV2,MobileNeXt,GhostNet,ParNet,MobileViT、AdderNet,ShuffleNetV1-V2,LCNet,etc. ⭐⭐⭐⭐⭐
PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.
An easy-to-use federated learning platform
This is the formal code implementation of the CVPR 2022 paper 'Federated Class Incremental Learning'.
联邦学习
A flexible Federated Learning Framework based on PyTorch, simplifying your Federated Learning research.
A Research-Industry integrated Federated Learning Library, backed by FedML, Inc (https://FedML.ai). Supporting distributed computing, mobile/IoT on-device training, and standalone simulation. Best Paper Award at NeurIPS 2020 Federated Learning workshop. Join our Slack Community:(https://join.slack.com/t/fedml/shared_invite/zt-havwx1ee-a1xfOUrATNfc9DFqU~r34w)
FedML-IoT: Federated Learning on IoT Devices (supported by FedML framework)
FedML-Server: Federated Learning Server for FedML-IoT and FedML-Mobile
FedScale: Benchmarking Model and System Performance of Federated Learning
FedUL: Federated Learning from Only Unlabeled Data with Class-Conditional-Sharing Clients
This repository gathers the materials of the FL-datasets public initiative.
Experiments on MNIST dataset and federated training using Flower framework
A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.
A lightweight LaTeX template for use with the IB Category 5 Internal Assessment based on the article class.
PyCIL: A Python Toolbox for Class-Incremental Learning
《Pytorch模型训练实用教程》中配套代码
Productive & portable high-performance programming in Python.
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Google 开源项目风格指南 (中文版)
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.