Results 161 to 170 of about 20,565,365 (293)
Distributed Nonparametric Regression with Heterogeneity Through Prediction-Based Aggregation. [PDF]
Chen Z, Li R, Xu Y.
europepmc +1 more source
A novel workflow for investigating hydride vapor phase epitaxy for GaN bulk crystal growth is proposed. It combines Design of experiments (DoE) with physical simulations of mass transport and crystal growth kinetics, serving as an intermediate step between DoE and experiments.
J. Tomkovič +7 more
wiley +1 more source
ConceptACT: episode-level concepts for sample-efficient robotic imitation learning. [PDF]
Karalus J, Schwenker F.
europepmc +1 more source
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari +5 more
wiley +1 more source
Design of a Sequential Filtering Method Fully Equivalent to the Centralized Filter with Cross-Correlated Noise. [PDF]
Huang Y, Huang W, Wen C.
europepmc +1 more source
Scandium (Sc)‐doped AlCoCrFeMo HEA coatings are fabricated via flame spraying with 0.1, 0.3, and 0.5 wt% Sc additions. Among these, the HEA‐Sc0.3 coating exhibits the highest corrosion resistance, indicated by a more positive corrosion potential and lower current density.
Pankaj Kumar +7 more
wiley +1 more source
Multidimensional Bayesian adaptive testing. [PDF]
Fink A, König C, Frey A.
europepmc +1 more source
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran +6 more
wiley +1 more source
Design of absorbing material distribution for noise barrier via accelerated BEM and optimality criteria method. [PDF]
Zhao A, Lei G, Jiang J, Ming H, Liu K.
europepmc +1 more source
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source

