Continuous monitoring of propofol in human serum with fouling compensation by support vector classifier

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Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...

This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SV ...

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Continuous monitoring of propofol in human serum with fouling compensation by support vector classifier

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Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Partial discharge localization in power transformer tanks using machine learning methods

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

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Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Random matrix methods for high-dimensional machine learning models

Error scaling laws for kernel classification under source and capacity conditions

DeepBreath-automated detection of respiratory pathology from lung auscultation in 572 pediatric outpatients across 5 countries

Towards Robust Monitoring of the Laser Powder Bed Fusion Process based on Acoustic Emission combined with Machine Learning Solutions

Euclid preparation XXII. Selection of quiescent galaxies from mock photometry using machine learning

Probabilistic methods for neural combinatorial optimization

Self-Supervised Bayesian representation learning of acoustic emissions from laser powder bed Fusion process for in-situ monitoring

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Behavioral outcome of very preterm children at 5 years of age: Prognostic utility of brain tissue volumes at term-equivalent-age, perinatal, and environmental factors

Segmenting Without Annotating: Crack Segmentation and Monitoring via Post-Hoc Classifier Explanations

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Learning From Heterogeneous Data Based on Social Interactions Over Graphs

Optimizing in-situ monitoring for laser powder bed fusion process: Deciphering acoustic emission and sensor sensitivity with explainable machine learning

Estimating and Improving the Robustness of Attributions in Text

Toward data-driven materials design: From atoms to pilot plants