Results 31 to 40 of about 1,258,060 (324)
The empirical process on Gaussian spherical harmonics [PDF]
, 2004 We establish weak convergence of the empirical process on the spherical harmonics of a Gaussian random field in the presence of an unknown angular power spectrum. This result suggests various Gaussianity tests with an asymptotic justification.
Domenico Marinucci +3 more
core +3 more sources
Multisensor Estimation Fusion with Gaussian Process for Nonlinear Dynamic Systems
Entropy, 2019 The Gaussian process is gaining increasing importance in different areas such as signal processing, machine learning, robotics, control and aerospace and electronic systems, since it can represent unknown system functions by posterior probability.
Yiwei Liao +3 more
doaj +1 more source
Conformations of Steroid Hormones: Infrared and Vibrational Circular Dichroism Spectroscopy
Molecules, 2023 Steroid hormone molecules may exhibit very different functionalities based on the associated functional groups and their 3D arrangements in space, i.e., absolute configurations and conformations.
Yanqing Yang +6 more
doaj +1 more source
Massively parallel approximate Gaussian process regression [PDF]
, 2014 We explore how the big-three computing paradigms -- symmetric multi-processor (SMC), graphical processing units (GPUs), and cluster computing -- can together be brought to bare on large-data Gaussian processes (GP) regression problems via a careful ...
Gramacy, Robert +3 more
core +4 more sources
Global Optimization Employing Gaussian Process-Based Bayesian Surrogates
Entropy, 2018 The simulation of complex physics models may lead to enormous computer running times. Since the simulations are expensive it is necessary to exploit the computational budget in the best possible manner.
Roland Preuss, Udo von Toussaint
doaj +1 more source
Journal of Asian Architecture and Building Engineering, 2021 With building energy codes getting strict, quantitative analysis is necessary in the early design stage of high-energy-performance buildings. To fully explore the design space, a highly efficient method is necessary.
Yun Gao +2 more
doaj +1 more source
Science and Technology for Energy TransitionSurrogate models have become a widely used solution for reducing computation times along design processes. In this work, a Gaussian Process surrogate model is built and used to predict the performance and losses of a wound field electrical machine in a ...
Mazloum Rebecca +5 more
doaj +1 more source
Ground Moving Target Tracking Filter Considering Terrain and Kinematics
Sensors, 2021 This paper addresses ground target tracking (GTT) for airborne radar. Digital terrain elevation data (DTED) are widely used for GTT as prior information under the premise that ground targets are constrained on terrain.
Do-Un Kim +5 more
doaj +1 more source
, 2020 We introduce a novel way to combine boosting with Gaussian process and mixed effects models. This allows for relaxing, first, the zero or linearity assumption for the prior mean function in Gaussian process and grouped random effects models in a flexible non-parametric way and, second, the independence assumption made in most boosting algorithms.
openaire +3 more sources
Data-Driven Approaches for Tornado Damage Estimation with Unpiloted Aerial Systems
Remote Sensing, 2021 Tornado damage estimation is important for providing insights into tornado studies and assisting rapid disaster response. However, it is challenging to precisely estimate tornado damage because of the large volumes of perishable data. This study presents
Zhiang Chen +4 more
doaj +1 more source