Results 101 to 110 of about 110,596 (265)
Advanced Functional Materials, EarlyView.Mask‐encoded UV exposure translates digital color information into pixel‐resolved structural‐color patterns in hydroxypropyl cellulose gels. Gaussian‐process‐guided calibration links UV processing conditions, wavelength, and mask opacity, enabling parallel fabrication of multicolor images in a single 10 s exposure.
Mengting Ye +8 more
wiley +1 more source
Advanced Functional Materials, EarlyView.Here, we establish a low‐dose liquid‐phase electron microscopy workflow for real‐time observation of biological processes in hydrated conditions. Beam damage is reduced by imaging only 20% of the pixels and reconstructing the complete image using an inpainting algorithm.
Luco Rutten +7 more
wiley +1 more source
The role of hyperparameters in machine learning models and how to tune them [PDF]
Hyperparameters critically influence how well machine learning models perform on unseen, out-of-sample data. Systematically comparing the performance of different hyperparameter settings will often go a long way in building confidence about a model's ...
Arnold, Christian; id_orcid +4 more
core +1 more source
Hyperparameters employed for network training.
, 2020 Hyperparameters employed for network training.
Helge Ritter (848600) +3 more
core +1 more source
, 2023 A listing of the hyperparameters that were held constant throughout the study. The values were set according to the implementation of https://github.com/AntixK/PyTorch-VAE. (PDF)
Mostafa Eltager (17102176) +5 more
core +1 more source
Advanced Materials, EarlyView.Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam +6 more
wiley +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
Advanced Materials, EarlyView.This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Prediction of Total Petroleum Hydrocarbons and Heavy Metals in Acid Tars Using Machine Learning
Applied SciencesHazardous petroleum wastes are an inevitable source of environmental pollution. Leachates from these wastes could contaminate soil and potable water sources and affect human health.
Mihaela Tita, Ion Onutu, Bogdan Doicin
doaj +1 more source
Data‐Driven Materials Science for Energy‐Sustainable Applications
Advanced Materials, EarlyView.Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley +1 more source
Hyperparameters: optimize, or integrate out?
, 1996 I examine two approximate methods for computational implementation of Bayesian hierarchical models, that is, models which include unknown hyperparameters such as regularization constants.
David J. C. MacKay
core +1 more source