Conservation of forest biomass and forest–dependent wildlife population: Uncertainty quantification of the model parameters by Fanuel, Ibrahim M., Mirau, Silas, Kajunguri, Damian, Moyo, Francis

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Prediction of the SYM‐H Index Using a Bayesian Deep Learning Method With Uncertainty Quantification by Yasser Abduallah, Khalid A. Alobaid, Jason T. L. Wang, Haimin Wang, Vania K. Jordanova, Vasyl Yurchyshyn, Huseyin Cavus, Ju Jing

“…In addition, SYMHnet can provide results for both data and model uncertainty quantification, whereas the related methods cannot.…”
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Bayesian calibration and uncertainty quantification for a large nutrient load impact modelZenodoZenodoZenodo by Karel Kaurila, Risto Lignell, Frede Thingstad, Harri Kuosa, Jarno Vanhatalo

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Global sensitivity analysis and uncertainty quantification for a mathematical model of dry anaerobic digestion in plug-flow reactors by Daniele Bernardo Panaro, Andrea Trucchia, Vincenzo Luongo, Maria Rosaria Mattei, Luigi Frunzo

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Global Sensitivity Analysis and Uncertainty Quantification for Background Solar Wind Using the Alfvén Wave Solar Atmosphere Model by Aniket Jivani, Nishtha Sachdeva, Zhenguang Huang, Yang Chen, Bart van derHolst, Ward Manchester, Daniel Iong, Hongfan Chen, Shasha Zou, Xun Huan, Gabor Toth

Subjects: “…uncertainty quantification…”
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Decent Estimate of CME Arrival Time From a Data‐Assimilated Ensemble in the Alfvén Wave Solar Atmosphere Model (DECADE‐AWSoM) by Hongfan Chen, Nishtha Sachdeva, Zhenguang Huang, Bart van derHolst, Ward Manchester IV, Aniket Jivani, Shasha Zou, Yang Chen, Xun Huan, Gabor Toth

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Composite Bayesian Optimization in function spaces using NEON—Neural Epistemic Operator Networks by Leonardo Ferreira Guilhoto, Paris Perdikaris

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Uncertainty quantification and global sensitivity analysis of turbulence model closure coefficients for sheet cavity flow around a hydrofoil by Simone Romani, Mitja Morgut, Lucia Parussini, Marzio Piller

Subjects: “…uncertainty quantification…”
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Parameter uncertainties for imperfect surrogate models in the low-noise regime by Thomas D Swinburne, Danny Perez

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A novel framework for uncertainty quantification of rainfall–runoff models based on a Bayesian approach focused on transboundary river basins by Thi-Duyen Nguyen, Duc Hai Nguyen, Hyun-Han Kwon, Deg-Hyo Bae

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Uncertainty Quantification for Machine Learning‐Based Ionosphere and Space Weather Forecasting: Ensemble, Bayesian Neural Network, and Quantile Gradient Boosting by Randa Natras, Benedikt Soja, Michael Schmidt

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Uncertainty quantification of rock mass discontinuity information and mechanical parameter derived from photogrammetry and Monte Carlo simulation: A case study by Xiaoyu Yi, Wenkai Feng, Yongjian Zhou, Wenxuan Wu, Jiachen Zhao

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Comment on “Prediction of the SYM‐H Index Using a Bayesian Deep Learning Method With Uncertainty Quantification” by Abduallah et al. (2024) by Armando Collado‐Villaverde, Pablo Muñoz, Consuelo Cid

“…Additionally, the network also provides an uncertainty quantification of the predictions. While the approach is innovative, there are some areas where the model's design and implementation may not align with best practices in uncertainty quantification and predictive modeling. …”
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Quantifying Uncertainties in the Quiet‐Time Ionosphere‐Thermosphere Using WAM‐IPE by Weijia Zhan, Alireza Doostan, Eric Sutton, Tzu‐Wei Fang

Subjects: “…uncertainty quantification…”
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A probabilistic model-based approach to assess and minimize scaling in geothermal plants by Pejman Shoeibi Omrani, Jonah Poort, Eduardo G. D. Barros, Hidde de Zwart, Cintia Gonçalves Machado, Laura Wasch, Aris Twerda, Huub H. M. Rijnaarts, Shahab Shariat Torbaghan

Subjects: “…Uncertainty quantification…”
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Fitting Geometric Shapes to Fuzzy Point Cloud Data by Vincent B. Verhoeven, Pasi Raumonen, Markku Åkerblom

Subjects: “…uncertainty quantification…”
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Improvements of particle filter optimization algorithm for robust optimization under different types of uncertainties by Éva Kenyeres, Alex Kummer, János Abonyi

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Ensemble Modeling of Radiation Belt Electron Acceleration by Chorus Waves: Dependence on Key Input Parameters by Man Hua, Jacob Bortnik, Adam C. Kellerman, Enrico Camporeale, Qianli Ma

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Blast loading prediction in a typical urban environment based on Bayesian deep learning by Weiwen Peng, Meilin Pan, Chunjiang Leng, Shufei Wang, Wei Zhong

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Finite strain formulation of the discrete equilibrium gap principle: application to direct parameter estimation from large full-fields measurements by Peyraut, Alice, Genet, Martin

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