Evaluation of the performance of the Light Gradient Boosting Machine (LightGBM) algorithm in predicting live weight in different goat breeds. [PDF]
Yavuz E.
europepmc +1 more source
Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su +13 more
wiley +1 more source
Development and Internal Validation of a Gradient Boosting Model for Pressure Injury Risk in the ICU. [PDF]
Qian S +9 more
europepmc +1 more source
Two‐dimensional CuInP2S6 nanosheets are incorporated into a P(VDF‐TrFE) matrix to induce polarization‐cooperative ferroelectric coupling. The resulting P(VDF‐TrFE)/CuInP2S6 hybrid film exhibits reinforced ferroelectric ordering and reduced coercive electric fields compared with pristine P(VDF‐TrFE).
Yeonsu Jeong +10 more
wiley +1 more source
Modelling the urban acoustic environment using land use-based gradient boosting. [PDF]
Haselhoff T +4 more
europepmc +1 more source
Study on the Reaction Mechanism of RuOx and Its Enhanced Hydrogen Evolution Reaction Activity
In situ Raman spectroscopy and DFT calculations reveal that, prior to the onset of HER, the surface of RuOx undergoes reversible reduction and structural reconstruction. The resulting Ru(II)O/Ru(IV)O2 configuration is identified as the true catalytically active species.
Liquan Zhang +9 more
wiley +1 more source
Gradient boosting-based discrete failure time model for selecting time-varying effects and interactions. [PDF]
Luo L, He K, Taylor JMG.
europepmc +1 more source
Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai +3 more
wiley +1 more source
An optimized gradient boosting framework for IoT intrusion detection: a comprehensive evaluation on the CICIoT2023 dataset. [PDF]
Almahaqeri SA +5 more
europepmc +1 more source
Wasserstein Gradient Boosting: A Framework for Distribution-Valued Supervised Learning
Gradient boosting is a sequential ensemble method that fits a new weaker learner to pseudo residuals at each iteration. We propose Wasserstein gradient boosting, a novel extension of gradient boosting that fits a new weak learner to alternative pseudo ...
Matsubara, Takuo
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