Results 181 to 190 of about 56,420 (266)

Advancing early detection of chromophobe renal cell carcinoma: a Bayesian optimization approach to machine learning models. [PDF]

Sci Rep
Chen Y, Zhou Q, Hussain L, Wei Y, Wang J, Xia T.   +5 more
europepmc   +1 more source

Imprecise Bayesian optimization

Knowledge-Based Systems
Julian Rodemann, Thomas Augustin 0001
openaire   +2 more sources

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

Advanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan, Imelda Cardenas‐Sierra, Pei Sun, Hari Raj, Daniele Duranti, Mahnoor Nafees, Edoardo Rossi, Marco Sebastiani, Paul Vigneaux, Martin Petit, Maxime Moreaud, Francisco Fernandez, Alejandro A. Franco   +12 more
wiley   +1 more source

Navigating Ternary Doping in Li-ion Cathodes With Closed-Loop Multi-Objective Bayesian Optimization. [PDF]

Adv Mater
Zeinali Galabi N, Liu CH, Jain M, Kamel M, Jia S, Bengio Y, McCalla E.   +6 more
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Data-Driven Design of Epoxy-Granite Machine Foundations: Bayesian Optimization for Enhanced Compressive Strength and Vibration Damping. [PDF]

Polymers (Basel)
Abdellah MY, Irfan OM, Omar HM.
europepmc   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

A manta ray-bayesian optimization approach for hyperparameter-tuned convolutional neural networks in lung cancer classification. [PDF]

Sci Rep
Samal S, Sunder S, Gadekellu TR, Yagin FH, Shawi RE, Ahmed N.   +5 more
europepmc   +1 more source

Farmers' Preferences for Gene Editing Crops and Influencing Factors

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT Gene editing (GE) is gaining momentum worldwide, but limited data on UK farmers' preferences hinders our understanding of its potential impact amid deregulation debates. Based on a survey of 200 English arable farmers, we employ a Latent Class Analysis and Multinomial Logit regressions to investigate current preferences for GE crops.
Bertolozzi‐Caredio Daniele, Vigani Mauro   +1 more
wiley   +1 more source

Autonomous Bayesian Optimization-Based Control System for Droplet Generation. [PDF]

Small Methods
Cho S, Kim H, Shin S, Lee M, Lee J.
europepmc   +1 more source