hui-zhang-adabella Goto Github PK

appfl

Advanced Privacy-Preserving Federated Learning framework

awesome-energy-forecasting

list of papers, code, and other resources

data_market

dem

Decentralized Energy Marketplace via NFTs and AI-based Agents

differential-privacy-based-federated-learning

Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shakespeare, mnist, cifar-10 and fashion-mnist. )

energy_consumption_prediction

Energy consumption prediction using LSTM/GRU networks in PyTorch

federated-learning

An open source FL implement with dataset(Femnist, Shakespeare, MNIST, Cifar-10 and Fashion-Mnist) using pytorch

federated-learning-and-differential-privacy

federated-learning-with-hyperparameter-based-clustering-for-electrical-load-forecasting

This code uses federated learning to forecast electrical power consumption of households while protecting data privacy.

fl-appliance-energy-prediction-and-classification

This repository houses a Federated Learning project that trains models to predict the energy use of appliances and classifies them accordingly

ldd-linuxdevicedrivers

Linux内核与设备驱动程序学习笔记

linux-scheduler

machine-learning-to-predict-energy-consumption

Building a machine learning model to predict energy consumption using LSTM (Long-Short Term Memory)

optimized_building_energy_consumption_prediction_with_machine_learning

Explore EMS for predicting Building Energy Consumption using Stacked Ensemble with Heap-Based Optimization (HBO). This innovative approach leverages corporate hierarchy insights to optimize model parameters and boost accuracy. See significant performance improvements compared to traditional methods.

transformer-based-federated-learning-for-load-forecasting

Source code for our ICCEP paper "Secure short-term load forecasting for smart grids with transformer-based federated learning".