The multiple condition (MC)-retention model is an uncertainty-aware graph-based neural network that predicts liquid chromatography (LC) retention times across multiple column chem ...
Visualization, Dimensionality Reduction, Reproducibility, Stability, Multivariate Quantum Data, Information Retrieval ...
In his doctoral thesis, Michael Roop develops numerical methods that allow finding physically reliable approximate solutions ...
Researchers at Skoltech have proposed a new approach to training neural networks for wave propagation in absorbing media. The ...
Abstract: This letter employs a derivative-free trust-region method to solve the norm-optimal iterative learning control problem for nonlinear systems with unknown dynamics. The iteration process is ...
ABSTRACT: The nearly analytic discretization of the frequency-domain wave equation produces large-scale, sparse, and ill-conditioned linear system, which challenge conventional iterative solvers. To ...
This manuscript presents important findings that challenge traditional models of speech processing by demonstrating that theta-gamma phase-amplitude coupling in the auditory cortex is primarily a ...
Abstract: This article presents a nonlinear modeling method for the flux linkage and torque of a switched reluctance motor. The method is based on universal weighted least squares support vector ...
Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...
A GCSE Maths video explaining how to solve equations using iteration. This video demonstrates how difficult equations can be solved by using an iterative formula over and over to get closer to the ...
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