The energy sector is becoming a highly connected cyber-physical ecosystem in which distributed energy resources, electric ...

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...

Atharv Kolhar, a staff test automation engineer at Figure AI, says the robotics industry needs a testing philosophy that ...

As patients are divided into ever more narrowly defined subgroups, the number of individuals available for research shrinks dramatically. While this approach improves personalization, it also creates ...

ABSTRACT: Bipolar disorder (BD) affects approximately 45 million individuals worldwide and is characterized by recurrent episodes of mania, hypomania, and depression, with an average diagnostic delay ...

Federated Learning (FL) is a distributed Machine Learning (ML) paradigm that enables multiple local devices, that is, clients, and a central server to collaboratively train a ML model using data ...

By exploring the synergistic integration of federated learning and blockchain, this review evaluates how BCFL enhances data security, supports privacy-preserving cross-institutional collaboration, and ...

If it feels like social platforms suddenly “get” you more than they used to, you’re not imagining it! In 2026, feeds aren’t only reacting to what you click anymore. They’re predicting what you ...

MIDN enables multiple healthcare institutions to collaboratively impute missing data without sharing raw patient data. Only aggregated statistics are exchanged, ensuring patient privacy while ...

This GitHub repository contains the code, data, and figures for the paper FedRAIN-Lite: Federated Reinforcement Algorithms for Improving Idealised Numerical Weather and Climate Models. Also includes ...