Results 151 to 160 of about 113,020 (264)

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

A parallel dual-stream state-space module for reliable and efficient biomedical relation extraction. [PDF]

PLoS Comput Biol
Jia Y, Yuan Z, Zhu L, Han B, Ren L, Xiang ZL.   +5 more
europepmc   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

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, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

What has been researched about implicit memory in speech-language-hearing pathology? A scoping review. [PDF]

Codas
Silva FRFRD, Leal GDC, Barabás RC, Nemr K.   +3 more
europepmc   +1 more source

Implicit Knowledge and Composite

Sen'i Gakkaishi, 2006
openaire   +2 more sources

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

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, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

A non-verbal process dissociation procedure to disentangle explicit from implicit sequence learning. [PDF]

Neurosci Conscious
Malassis R, Moscado L, Sackur J, Németh D.   +3 more
europepmc   +1 more source

Participants' above-chance recognition of own-heart sound combined with poor metacognitive awareness suggests implicit knowledge of own heart cardiodynamics. [PDF]

Sci Rep, 2016
Azevedo RT, Aglioti SM, Lenggenhager B.
europepmc   +1 more source

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

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, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

Knowledge Distillation of a Protein Language Model Yields a Foundational Implicit Solvent Model. [PDF]

J Chem Theory Comput
Airas J, Zhang B.
europepmc   +1 more source