Results 191 to 200 of about 19,135,649 (331)
The hybrid approach to Quantum Supervised Machine Learning is compatible with Noisy Intermediate Scale Quantum (NISQ) devices but hardly useful. Pure quantum kernels requiring fault‐tolerant quantum computers are more promising. Examples are kernels computed by means of the Quantum Fourier Transform (QFT) and kernels defined via the calculation of ...
Massimiliano Incudini+2 more
wiley +1 more source
ABSTRACT In privacy protection of control systems, a trade‐off between control performance and privacy level is often pointed out. Our goal in this paper is to improve this trade‐off by shaping the frequency of noise added for privacy protection when the control objective is to track a reference signal, which is taken as a piece of information whose ...
Rintaro Watanabe+3 more
wiley +1 more source
A generative AI model for super‐resolution microscopy images is presented. Super‐resolution microscopy provides high spatial detail at the expense of lower time resolution. Using it for live samples requires computational image reconstruction. It is unclear what good priors and metrics for AI‐generated super‐resolution images are.
Meri Abgaryan+5 more
wiley +1 more source
Long non‐coding RNAs (lncRNAs) are receiving increasing attention as biomarkers for cancer diagnosis and therapy, highlighting the urgent need for computational methods to accelerate their comprehensive discovery. Here, to better predict and provide functional insight into cancer lncRNAs, a novel interpretable machine‐learning method (POCALI) is ...
Ziyan Rao+5 more
wiley +1 more source
Strong unique continuation of eigenfunctions for p‐Laplacian operator [PDF]
Islam Eddine Hadi, Najib Tsouli
openalex +1 more source
Thermal imaging offers a non‐destructive approach to quality control in silicon‐based lithium‐ion battery electrodes, enabling the detection of defects, variations in mass loading, and the monitoring of drying dynamics. This study introduces an automated defect‐detection‐algorithm and a machine learning‐based Random Forest model to estimate mass ...
Adil Amin+4 more
wiley +1 more source
Isolation and simplicity for the first eigenvalue of the p‐Laplacian with a nonlinear boundary condition [PDF]
Sandra Martı́nez, Julio D. Rossi
openalex +1 more source
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma+4 more
wiley +1 more source
Existence of periodic solution for fourth-order generalized neutral p-Laplacian differential equation with attractive and repulsive singularities. [PDF]
Xin Y, Liu H.
europepmc +1 more source