Post hoc uncertainty quantification for remote sensing observing systems

A Braverman, J Hobbs, J Teixeira, M Gunson - SIAM/ASA Journal on …, 2021 - SIAM
This article sets forth a practical methodology for uncertainty quantification of physical state
estimates derived from remote sensing observing systems. Remote sensing instruments …

Forward model emulator for atmospheric radiative transfer using Gaussian processes and cross validation

O Lamminpää, J Susiluoto, J Hobbs… - Atmospheric …, 2025 - amt.copernicus.org
Remote sensing of atmospheric carbon dioxide (CO2) carried out by NASA's Orbiting
Carbon Observatory-2 (OCO-2) satellite mission and the related uncertainty quantification …

Spectroscopic uncertainty impacts on OCO-2/3 retrievals of XCO2

JM Hobbs, BJ Drouin, F Oyafuso, VH Payne… - Journal of Quantitative …, 2020 - Elsevier
Estimates of atmospheric carbon dioxide concentration from satellites now span multiple
years and are providing information on key processes in the carbon cycle. Methodology for …

Objective Frequentist Uncertainty Quantification for Atmospheric Retrievals

P Patil, M Kuusela, J Hobbs - SIAM/ASA Journal on Uncertainty Quantification, 2022 - SIAM
The steadily increasing amount of atmospheric carbon dioxide () is affecting the global
climate system and threatening the long-term sustainability of Earth's ecosystem. In order to …

Automatic Dynamic Relevance Determination for Gaussian process regression with high-dimensional functional inputs

L Damiano, M Johnson, J Teixeira, MD Morris… - arXiv preprint arXiv …, 2022 - arxiv.org
In the context of Gaussian process regression with functional inputs, it is common to treat the
input as a vector. The parameter space becomes prohibitively complex as the number of …

Evaluating the accuracy of Gaussian approximations in VSWIR imaging spectroscopy retrievals

KM Leung, DR Thompson, J Susiluoto… - … on Geoscience and …, 2024 - ieeexplore.ieee.org
The joint retrieval of surface reflectances and atmospheric parameters in visible/short-wave
infrared (VSWIR) imaging spectroscopy is a computationally challenging high-dimensional …

Forward Model Emulator for Atmospheric Radiative Transfer Using Gaussian Processes And Cross Validation

OM Lamminpää, JI Susiluoto, JM Hobbs… - Atmospheric …, 2024 - amt.copernicus.org
Remote sensing of atmospheric carbon dioxide (CO 2) carried out by NASA's Orbiting
Carbon Observatory-2 (OCO-2) satellite mission and the related Uncertainty Quantification …

[HTML][HTML] Simulation Calculation of Element Number Density in the Earth's Atmosphere Based on X-ray Occultation Sounding

D Yu, B Li - Remote Sensing, 2022 - mdpi.com
The number density profiles of elements N and O in the altitude range of 120–250 km are
retrieved by simulation based on X-ray occultation. Based on the parameters of the NICER …

A Machine Learning Based Approach to Accelerate Catalyst Discovery

AJ Chowdhury - 2020 - search.proquest.com
Computational catalysis, in contrast to experimental catalysis, uses approximations such as
density functional theory (DFT) to compute properties of reaction intermediates. But DFT …

[引用][C] THE EXPONENTIAL WEIGHT FUNCTIONS FOR GAUSSIAN PROCESS REGRESSION WITH FUNCTIONAL INPUTS

L Damiano, M Johnson, J Teixeira, MD Morris, J Niemi - … relevance determination for …, 2023