Results 1 to 10 of about 823,786 (262)
Direct Sampling for Recovering Sound Soft Scatterers from Point Source Measurements
Computation, 2021 In this paper, we consider the inverse problem of recovering a sound soft scatterer from the measured scattered field. The scattered field is assumed to be induced by a point source on a curve/surface that is known.
Isaac Harris
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A Direct Sampling Method for the Inversion of the Radon Transform [PDF]
SIAM Journal on Imaging Sciences, 2021 We propose a novel direct sampling method (DSM) for the effective and stable inversion of the Radon transform. The DSM is based on a generalization of the important almost orthogonality property in classical DSMs to fractional order Sobolev duality products and to a new family of probing functions. The fractional order duality product proves to be able
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Analyses of Sampling Disturbance of the Lunar Surface in Direct Push Sampling Method
IEEE Access, 2018 The study of direct push sampling characteristics forms the theoretical basis for deep sampling tool design. In this paper, a ground test of the direct push sampling was carried out to analyze three influencing factors: tube diameter; friction ...
Dewei Tang +4 more
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Negative result of multi-frequency direct sampling method in microwave imaging
Results in Physics, 2019 A negative result of multi-frequency direct sampling method (DSM) for imaging small anomaly from scattering parameters in microwave imaging was exhibited.
Won-Kwang Park
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Direct Sampling Method for Diffusive Optical Tomography [PDF]
SIAM Journal of Scientific Computing, 2015 In this work, we are concerned with the diffusive optical tomography (DOT) problem in the case when only one or two pairs of Cauchy data is available. We propose a simple and efficient direct sampling method (DSM) to locate inhomogeneities inside a homogeneous background and solve the DOT problem in both full and limited aperture cases. This new method
Keji Liu, , Kazufumi Itô
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Optimistic Information Directed Sampling
CoRR, 2023 We study the problem of online learning in contextual bandit problems where the loss function is assumed to belong to a known parametric function class. We propose a new analytic framework for this setting that bridges the Bayesian theory of information-directed sampling due to Russo and Van Roy (2018) and the worst-case theory of Foster, Kakade, Qian,
Neu G., Papini M., Schwartz L.
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Frontiers in Earth Science, 2023 One of the major problems in the volcanic surveillance is how data from several techniques can be correlated and used to discriminate between possible precursors of volcanic eruptions and changes related to non-eruptive processes.
Susana Layana +14 more
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Contextual Information-Directed Sampling
CoRR, 2022 Information-directed sampling (IDS) has recently demonstrated its potential as a data-efficient reinforcement learning algorithm. However, it is still unclear what is the right form of information ratio to optimize when contextual information is available.
Botao Hao, Tor Lattimore, Chao Qin
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Journal of Advances in Modeling Earth Systems, 2023 Resampling‐based weather generators simulate new time series of weather variables by reordering the observed values such that the statistics of the simulated data are consistent with the observed ones.
Jorge Guevara +10 more
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Conditioning Multiple‐Point Statistics Simulation to Inequality Data
Earth and Space Science, 2021 Stochastic modeling is often employed in environmental sciences for the analysis and understanding of complex systems. For example, random fields are key components in uncertainty analysis or Bayesian inverse modeling.
Julien Straubhaar, Philippe Renard
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