Results 101 to 110 of about 196,185 (268)
GAUSSIAN PROCESSES FOR MACHINE LEARNING [PDF]
Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many deep theoretical analyses of various properties are available. This paper gives an introduction to Gaussian processes
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A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle +5 more
wiley +1 more source
SCADA based nonparametric models for condition monitoring of a wind turbine
High operation and maintenance costs for offshore wind turbines push up the LCOE of offshore wind energy. Unscheduled maintenance due to unanticipated failures is the most prominent driver of the maintenance cost which reinforces the drive towards ...
Ravi Kumar Pandit +2 more
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Experiments and thermophysical simulations were conducted to investigate the electron beam powder bed fusion electron beam (PBF‐EB/M) process for the γ′‐strengthened nickel‐based superalloy Inconel 738LC. The results demonstrate the impact of process‐induced microstructural variations on high‐temperature mechanical behavior, providing a basis for ...
Jan Niklas Petenati +11 more
wiley +1 more source
POLYNOMIAL-GAUSSIAN VECTORS AND POLYNOMIAL-GAUSSIAN PROCESSES
Let \({\mathbf X}_d=(X_1,\dots, X_d)\) denote a \(d\)-dimensional r.v., the density of which is a product of a nonnegative polynomial in \(x_1\) and a \(d\)-dimensional Gaussian density. \({\mathbf X}_d\) has a \(d\)-dimensional polynomial-Gaussian distribution \((\text{PGD}_d)\).
Plucińska, Agnieszka, Bisińska, Monika
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During creep of a single‐crystal Ni‐based superalloy, the overall crystal orientation is observed to remain constant while the microstructure evolves. Despite the lack of macroscopic rotation, small (<1°) rotations are observed on the submicron size scale and are accommodated by counteracting rotations over the scale of several micrometers.
E. J. Payton +3 more
wiley +1 more source
Characterisation of promoters, repressors, enhancers and so on, is not only essential for unravelling the inner workings of gene regulation, but also to enable the rational engineering of novel synthetic elements. Each putative regulatory region requires
Konstantinos Markakis +2 more
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Residual adhesive after electrode loading in adhesive‐assisted resistance spot welding is quantified through a traceable experimental‐to‐digital workflow. Chromatic confocal topography provides calibrated surface‐height data, while OpenCV detects the electrode imprint and integrates adhesive height into comparable volume metrics.
Sung‐Min Wi, Jiangdong Zhao
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Deep‐UV (258 nm) femtosecond pulses enable uniform amorphous silicon writing on Si(100)/(111) with a six‐fold larger fluence amorphization window than NIR methods. Optimized fluence and overlap yield 20–45 nm uniform and continuous amorphous layers. Microscopy shows sharp interfaces, and real‐time reflectivity reveals nanosecond melt–resolidification ...
Wissal Benali +5 more
wiley +1 more source
Gaussian Process Landmarking on Manifolds
As a means of improving analysis of biological shapes, we propose an algorithm for sampling a Riemannian manifold by sequentially selecting points with maximum uncertainty under a Gaussian process model. This greedy strategy is known to be near-optimal in the experimental design literature, and appears to outperform the use of user-placed landmarks in ...
Tingran Gao +2 more
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