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Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

open access: yesAdvanced Science, EarlyView.
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
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Exploring Privileged Features for Relation Extraction With Contrastive Student-Teacher Learning

IEEE Transactions on Knowledge and Data Engineering, 2022
Qiang Qu, Jinke Li, Ruifeng Xu
exaly  

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