Results 31 to 40 of about 14,298 (230)
On a Robust MaxEnt Process Regression Model with Sample-Selection
Entropy, 2018 In a regression analysis, a sample-selection bias arises when a dependent variable is partially observed as a result of the sample selection. This study introduces a Maximum Entropy (MaxEnt) process regression model that assumes a MaxEnt prior ...
Hea-Jung Kim, Mihyang Bae, Daehwa Jin
doaj +1 more source
Design of Amorphous Carbon Coatings Using Gaussian Processes and Advanced Data Visualization
Lubricants, 2022 In recent years, an increasing number of machine learning applications in tribology and coating design have been reported. Motivated by this, this contribution highlights the use of Gaussian processes for the prediction of the resulting coating ...
Christopher Sauer +5 more
doaj +1 more source
Kernel-based Information Criterion
, 2014 This paper introduces Kernel-based Information Criterion (KIC) for model selection in regression analysis. The novel kernel-based complexity measure in KIC efficiently computes the interdependency between parameters of the model using a variable-wise ...
Danafar, Somayeh +2 more
core +3 more sources
Winter Wheat Nitrogen Estimation Based on Ground-Level and UAV-Mounted Sensors
Sensors, 2022 A better understanding of wheat nitrogen status is important for improving N fertilizer management in precision farming. In this study, four different sensors were evaluated for their ability to estimate winter wheat nitrogen.
Xiaoyu Song +5 more
doaj +1 more source
Machine learning with systematic density-functional theory calculations: Application to melting temperatures of single and binary component solids [PDF]
, 2014 A combination of systematic density functional theory (DFT) calculations and machine learning techniques has a wide range of potential applications.
Maekawa, Tomoya +3 more
core +2 more sources
Neural Computing and Applications, 2022 Solar energy technologies represent a viable alternative to fossil fuels for meeting increasing global energy demands. However, to increase the production of solar technologies in the global energy mix, the cost of production should be as competitive as other sources.
Humphrey Adun +8 more
openaire +2 more sources
Unsupervised Domain Adaptation with Copula Models
, 2017 We study the task of unsupervised domain adaptation, where no labeled data from the target domain is provided during training time. To deal with the potential discrepancy between the source and target distributions, both in features and labels, we ...
Pavlovic, Vladimir +2 more
core +1 more source
Engine Emission Prediction Based on Extrapolated Gaussian Process Regression Method
Shanghai Jiaotong Daxue xuebao, 2022 Aimed at improving the prediction accuracy of engine emissions under driving conditions which are not covered by the training set, an extrapolated Gaussian process regression (GPR) method is proposed.
WANG Ziyao, GUO Fengxiang, CHEN Li
doaj +1 more source
Gaussian Process Regression for Estimating EM Ducting Within the Marine Atmospheric Boundary Layer
, 2019 We show that Gaussian process regression (GPR) can be used to infer the electromagnetic (EM) duct height within the marine atmospheric boundary layer (MABL) from sparsely sampled propagation factors within the context of bistatic radars.
Earls, Christopher J., Sit, Hilarie
core +1 more source
, 2020 Hypertension is a potentially unsafe health ailment, which can be indicated directly from the Blood pressure (BP). Hypertension always leads to other health complications. Continuous monitoring of BP is very important; however, cuff-based BP measurements
Chowdhury, Moajjem Hossain +6 more
core +1 more source