Results 101 to 110 of about 167,613,033 (239)
Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez +4 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
Implicit Theories of Mental Skills Abilities in Collegiate Athletes
, 2015 We aimed at studying athletes' mental skills-related implicit beliefs and their susceptibility to changes. Collegiate athletes (n= 68) responded to the Theories of Mental Skills scale to determine their implicit beliefs of mental skills abilities within ...
Eklund, Robert +2 more
core +1 more source
Advanced Intelligent Discovery, EarlyView.Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
, 2017 This is a study about the beliefs novice teachers hold about their own self-efficacy for teaching, their personal implicit theories of intelligence, and the influence those beliefs might have on new teachers’ intentions to remain in the teaching ...
Feldstein, Linda E.
core +1 more source
MolMiner: Toward Controllable, Three‐Dimensional‐Aware, Fragment‐Based Molecular Design
Advanced Intelligent Discovery, EarlyView.MolMiner is a fragment‐based, geometry‐aware, and order‐agnostic generative model for molecular design with strong inductive biases. Using symmetry‐aware fragment assembly, dynamic three‐dimensional geometry, and multi‐property conditioning, MolMiner enables interpretable and controllable molecular generation.
Raul Ortega‐Ochoa +2 more
wiley +1 more source
Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction
Advanced Intelligent Discovery, EarlyView.Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong +4 more
wiley +1 more source
Theories of Wage Rigidity [PDF]
This paper considers two sets of theories attempting to explain wage rigidities and unemployment: implicit contract theory and the efficiency wage theory.
Joseph E. Stiglitz
core
Frontiers in PsychologyIntroductionThis study aimed to adapt the Mentor Mindset Scale into Turkish and examine its psychometric properties. The scale assesses mentors’ orientations toward youth as Enforcer and Protector, conceptualizing Mentor Mindset as a pattern defined by ...
Burhanettin Ozdemir +1 more
doaj +1 more source