To learn about real world phenomena, scientists have traditionally used models with clearly
interpretable elements. However, modern machine learning (ML) models, while powerful …

Automated machine learning (AutoML) was formed around the fundamental objectives of
automatically and efficiently configuring machine learning (ML) workflows, aiding the …

Phosphorus is a nonrenewable material essential for ensuring food security whose global
reserves are controlled by a limited number of nations. Potential phosphorus insecurity …

The pseudo-direct numerical simulation (P-DNS) method is a recently developed multiscale
strategy designed for high-fidelity computational simulation of complex flow physics. This …

Feature-based explanations, using perturbations or gradients, are a prevalent tool to
understand decisions of black box machine learning models. Yet, differences between these …

Tree-based learning methods such as Random Forest and XGBoost are still the gold-
standard prediction methods for tabular data. Feature importance measures are usually …

The destructive impacts of Wildland-Urban Interface (WUI) fires on people, property and the
environment have dramatically increased, especially in California. Critical factors influencing …

Abstract Machine learning (ML) models are increasingly being deployed in critical domains
such as healthcare, finance, marketing, autonomous vehicles, and energy. As these models …

Em uma sociedade cada vez mais conectada, na qual a Inteligência Artificial se
desenvolve a passos largos, o uso de tecnologias digitais como internet e computadores …