Zobrazeno 1 - 10
of 160
pro vyhledávání: '"LEE, ANN B."'
An open scientific challenge is how to classify events with reliable measures of uncertainty, when we have a mechanistic model of the data-generating process but the distribution over both labels and latent nuisance parameters is different between tr
Externí odkaz:
http://arxiv.org/abs/2402.05330
Prediction algorithms, such as deep neural networks (DNNs), are used in many domain sciences to directly estimate internal parameters of interest in simulator-based models, especially in settings where the observations include images or complex high-
Externí odkaz:
http://arxiv.org/abs/2205.15680
Because geostationary satellite (Geo) imagery provides a high temporal resolution window into tropical cyclone (TC) behavior, we investigate the viability of its application to short-term probabilistic forecasts of TC convective structure to subseque
Externí odkaz:
http://arxiv.org/abs/2206.00067
Autor:
Dey, Biprateep, Zhao, David, Andrews, Brett H., Newman, Jeffrey A., Izbicki, Rafael, Lee, Ann B.
There is a growing interest in conditional density estimation and generative modeling of a target $y$ given complex inputs $\mathbf{x}$. However, off-the-shelf methods often lack instance-wise calibration -- that is, for individual inputs $\mathbf{x}
Externí odkaz:
http://arxiv.org/abs/2205.14568
Autor:
Marcus, Brian S., Perez-Kersey, Plicy, Lee, Ann B., Jensen, Richard A., Dullanty, Beth S., Parrish, Patrick R., Park, Matthew V., Tressel, William, Kronmal, Richard, Schultz, Amy H.
Publikováno v:
In The Journal of Pediatrics: Clinical Practice December 2024 14
Our goal is to quantify whether, and if so how, spatio-temporal patterns in tropical cyclone (TC) satellite imagery signal an upcoming rapid intensity change event. To address this question, we propose a new nonparametric test of association between
Externí odkaz:
http://arxiv.org/abs/2202.02253
Autor:
Dey, Biprateep, Newman, Jeffrey A., Andrews, Brett H., Izbicki, Rafael, Lee, Ann B., Zhao, David, Rau, Markus Michael, Malz, Alex I.
Many astrophysical analyses depend on estimates of redshifts (a proxy for distance) determined from photometric (i.e., imaging) data alone. Inaccurate estimates of photometric redshift uncertainties can result in large systematic errors. However, pro
Externí odkaz:
http://arxiv.org/abs/2110.15209
Tropical cyclone (TC) intensity forecasts are issued by human forecasters who evaluate spatio-temporal observations (e.g., satellite imagery) and model output (e.g., numerical weather prediction, statistical models) to produce forecasts every 6 hours
Externí odkaz:
http://arxiv.org/abs/2109.12029
Publikováno v:
Electronic Journal of Statistics Vol. 18 | No. 2 (2024)
Many areas of science rely on simulators that implicitly encode intractable likelihood functions of complex systems. Classical statistical methods are poorly suited for these so-called likelihood-free inference (LFI) settings, especially outside asym
Externí odkaz:
http://arxiv.org/abs/2107.03920
There has been growing interest in the AI community for precise uncertainty quantification. Conditional density models f(y|x), where x represents potentially high-dimensional features, are an integral part of uncertainty quantification in prediction
Externí odkaz:
http://arxiv.org/abs/2102.10473