In recent years, the frequency of weather-related natural disasters—cyclones, torrential rains, floods—has increased as a ...

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

Food System Innovations has launched an open-source Food Intelligence Lab to use AI to create better-tasting alternative ...

Abstract: A fast and reliable nuclide identification algorithm is important to the detection of radioactive materials, and the emergence of a sequential Bayesian algorithm provides a new direction of ...

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PyBADS is a Python implementation of the Bayesian Adaptive Direct Search (BADS) algorithm for solving difficult and mildly expensive optimization problems, originally implemented in MATLAB. BADS has ...

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Quantum designers: Florian Marquardt (left) and Leopoldo Sarra have shown how deep Bayesian experimental design can be applied to quantum many-body systems. (Courtesy: Leopoldo Sarra) As quantum ...

Introduction: The retrospective analysis of continuous glucose monitoring (CGM) timeseries can be hampered by colored and non-stationary measurement noise. Here, we introduce a Bayesian denoising (BD) ...