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Health data privacy through homomorphic encryption and distributed ledger computing: an ethical-legal qualitative expert assessment study

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Health data privacy through homomorphic encryption and distributed ledger computing: an ethical-legal qualitative expert assessment study

Chat with Graph Search

Clinical trials for implantable neural prostheses: understanding the ethical and technical requirements

Towards General-Purpose Decentralized Computing with Permissionless Extensibility

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

On the fundamental limits of privacy-enhancing technologies

A compact approach to higher-resolution resonant inelastic x-ray scattering detection using photoelectrons

A Privacy-Preserving Querying Mechanism with High Utility for Electric Vehicles

High brightness neutron source optimized for very high pulsed magnetic field experiments

The Privacy Power of Correlated Noise in Decentralized Learning

Voices from the Frontline: Revealing the AI Practitioners' viewpoint on the European AI Act

Smart Proofs via Recursive Information Gathering: Decentralized Refereeing by Smart Contracts

Planetary-Scale Byzantine Fault Tolerance

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Explainability as fig leaf? An exploration of experts’ ethical expectations towards machine learning in psychiatry

Sustainability and Ethicality are Peripheral to Students’ Software Design

Bridging the gap between theoretical and practical privacy technologies for at-risk populations

Toward contactless human thermal monitoring: A framework for Machine Learning-based human thermo-physiology modeling augmented with computer vision

Scalable and Privacy-Preserving Federated Principal Component Analysis

Aerosol optical absorption coefficients at seven wavelengths in 10 min resolution measured in the Swiss container during MOSAiC 2019/2020

Challenging the Assumptions: Rethinking Privacy, Bias, and Security in Machine Learning

Personalized Privacy-Preserving Distributed Learning on Heterogeneous Data