EurekAlert!

New uncertainty-aware AI framework could improve fuel cell degradation forecasting

Researchers have developed an uncertainty quantification-based framework for predicting degradation trends in proton exchange ...
InfoQ

Amazon Releases Fortuna, an Open-Source Library for ML Model Uncertainty Quantification

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
University of Sheffield

Jonathan Owen

I am a Postdoctoral Research Associate working on the NERC funded project “Aerosol-MFR: Towards Maximum Feasible Reduction in Aerosol Forcing Uncertainty”, working with Dr Jill Johnson and Prof Jeremy ...
Semiconductor Engineering

Memory Devices-Based Bayesian Neural Networks For Edge AI

A new technical paper titled “Bringing uncertainty quantification to the extreme-edge with memristor-based Bayesian neural networks” was published by researchers at Université Grenoble Alpes, CEA, ...
Design-Reuse

CEA-Leti Paper in Nature Communications Reports First Complete Memristor-Based Bayesian Neural Network Implementation For Real-World Task

GRENOBLE, France – Dec. 7, 2023 – A team comprising CEA-Leti, CEA-List and two CNRS laboratories has published a new paper in Nature Communications presenting the first complete memristor-based ...
technologynetworks

An Introduction to Bayesian Statistics

In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...