In recent years, the frequency of weather-related natural disasters—cyclones, torrential rains, floods—has increased as a consequence of global warming. These disasters cause billions of dollars in ...

Black-box optimization, particularly Bayesian optimization, is a practical approach for weather-intervention design, achieving meaningful rainfall ...

ABSTRACT: This work introduces a novel Bayesian inspired regression method for the simultaneous estimation of model parameters and data uncertainties. The key mathematical result of this framework is ...

This is a research/educational demonstration project. Not for production decisions or control systems. Models are for demonstration purposes only Results should not be used for critical ...

This article is a Python coding record of Part 3, Chapter 6: 'Dummy Variables and ANOVA Models' from the book 'Introduction to Data Analysis with Bayesian Statistical Modeling using R and Stan'. Part ...

SALT LAKE CITY--(BUSINESS WIRE)--Palladyne AI (NASDAQ: PDYN), a U.S.-based defense and industrial technology company commercializing embedded AI, collaborative autonomy, and advanced avionics for ...

The ongoing massive investments in artificial intelligence (AI) aim to satisfy a huge increase in anticipated demand, which in turn has led some firms to offer rosy growth forecasts. To assess these ...

Abstract: Safe Bayesian optimization (BO) with Gaussian processes is an effective tool for tuning control policies in safety-critical real-world systems, specifically due to its sample efficiency and ...

A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool ...

Mobile health (mHealth) programs face a critical challenge in optimizing the timing of automated health information calls to beneficiaries. This challenge has been formulated as a collaborative ...