Abstract: Bayesian optimization (BO) is a framework for global optimization of expensive-to-evaluate objective functions. Classical BO methods assume that the objective function is a black box.

This Unity asset provides an end-to-end, Human-in-the-Loop (HITL) Multi-Objective Bayesian Optimization (MOBO) workflow built on botorch.org. It lets you declare design parameters and objectives in ...

Accurate prediction of crown convergence in Tunnel Boring Machine (TBM) tunnels is critical for ensuring construction safety, optimizing support design, and improving construction efficiency. This ...

Department of Engineering, University of Cambridge, Cambridge CB2 1CB2 1PZ, U.K.

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

Next to the primary optimization objectives, scientific optimization problems often contain a series of subordinate objectives, which can be expressed as preferences over either the outputs of an ...

Identifying lithology is crucial for geological exploration, and the adoption of artificial intelligence is progressively becoming a refined approach to automate this process. A key feature of this ...

ABSTRACT: Soil-water characteristic curve (SWCC) is significant to estimate the site-specific unsaturated soil properties (such as unsaturated shear strength and coefficient of permeability) for ...

While the majority of stroke researchers use frequentist statistics to analyze and present their data, Bayesian statistics are becoming more and more prevalent in stroke research. As opposed to ...