Explore how AI transforms crash tests and factory design, enhancing safety, efficiency, and innovation in automotive manufacturing.

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 ...

Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...

Many controlled processes, such as biochemical ones, are repetitive, similar to batch-organized processes. They generate Optimal Control Problems (OCPs) solved by optimal controllers, which often ...

Abstract: Structure learning of Bayesian networks is a well-researched but computationally hard task. For learning Bayesian networks, this paper proposes an improved algorithm based on unconstrained ...

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 ...

Department of Intelligent Energy and Industry, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea Department of Intelligent Energy and Industry, Chung-Ang University, 84 ...

SMAC offers a robust and flexible framework for Bayesian Optimization to support users in determining well-performing hyperparameter configurations for their (Machine Learning) algorithms, datasets ...