Using Bayesian analysis to quantify and reduce uncertainty in experimental measurements — A narrow-angle radiometer case study by Teri S. Draper, Jennifer P. Spinti, Philip J. Smith, Terry A. Ring, Eric G. Eddings

Subjects: “…Bayesian uncertainty quantification…”
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Sensitivity analysis and uncertainty quantification of climate change effects on Tanzanian banana crop yield by Sabas Patrick, Silas Mirau, Isambi Mbalawata, Judith Leo

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Artificial intelligence - finite element method - hybrids for efficient nonlinear analysis of concrete structures by Michael A. Kraus, Rafael Bischof, Walter Kaufmann, Karel Thoma

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Multimodal AI-driven object detection with uncertainty quantification for cardiovascular risk assessment in autistic patients by Ling Tang, Chengchao Shen

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Bridging Hydrological Ensemble Simulation and Learning Using Deep Neural Operators by Alexander Y. Sun, Peishi Jiang, Pin Shuai, Xingyuan Chen

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Uncertainty-Based Fusion Method for Structural Modal Parameter Identification by Xiaoteng Liu, Zirui Dong, Hongxia Ji, Zhenjiang Yue, Jie Kang

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Enhancing mental health diagnostics through deep learning-based image classification by Lixin Zhang, Ruotong Zeng

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Federated Bayesian Deep Learning: The Application of Statistical Aggregation Methods to Bayesian Models by John Fischer, Marko Orescanin, Justin Loomis, Patrick Mcclure

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A New Two‐Stage Probabilistic Remaining Useful Life Prediction Method for Wind Turbines by Weifei Hu, Xuewei Zhou, Qing Jiao, Feng Zhao, Ning Tang, Ke Li, Zili Wang

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Reduced-Order Models and Conditional Expectation: Analysing Parametric Low-Order Approximations by Hermann G. Matthies

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Uncertainty-Aware Parking Prediction Using Bayesian Neural Networks by Alireza Nezhadettehad, Arkady Zaslavsky, Abdur Rakib, Seng W. Loke

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Impacts of Spatial Expansion of Urban and Rural Construction on Typhoon-Directed Economic Losses: Should Land Use Data Be Included in the Assessment? by Siyi Zhou, Zikai Zhao, Jiayue Hu, Fengbao Liu, Kunyuan Zheng

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Multimodal deep learning for enhanced temperature prediction with uncertainty quantification in directed energy deposition (DED) process by Adrian Matias Chung Baek, Taehwan Kim, Minkyu Seong, Seungjae Lee, Hogyeong Kang, Eunju Park, Im Doo Jung, Namhun Kim

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Thermo‐Electro‐Mechanical Modeling of Failure: Application to Long‐Term Reliability of Aging Transmission Lines by Eduardo A. Barros De Moraes, K. C. Prakash, Mohsen Zayernouri

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Transforming Building Energy Management: Sparse, Interpretable, and Transparent Hybrid Machine Learning for Probabilistic Classification and Predictive Energy Modelling by Yiping Meng, Yiming Sun, Sergio Rodriguez, Binxia Xue

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Empirical validation of size effects in sub-sized tensile specimens for nuclear structural materials by Longze Li, John W. Merickel, Yalei Tang, Rongjie Song, Joshua E. Rittenhouse, Aleksandar Vakanski, Fei Xu

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Neural networks for reconstruction and uncertainty quantification of fast-ion phase-space distributions using FILD and INPA measurements by B. S. Schmidt, J. Rueda-Rueda, J. Galdon-Quíroga, M. García-Muñoz, P. A. Schneider, M. Salewski, the ASDEX Upgrade Team

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Efficient Adaptive Robust Aerodynamic Design Optimization Considering Uncertain Inflow Variations for a Diffusion Airfoil Across All Operating Incidences by Zhengtao Guo, Lei Bao, Chaolong Li, Xianzhong Gao, Wuli Chu

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A Physics-Guided Bayesian Neural Network for Sensor Fault Detection in Wind Turbines by MD Azam Khan, Arifur Rahman, Farhad Uddin Mahmud, Kanchon Kumar Bishnu, Hadiur Rahman Nabil, M. F. Mridha, Md. Jakir Hossen

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Uncertainty CNNs: A path to enhanced medical image classification performance by Vasileios E. Papageorgiou, Georgios Petmezas, Pantelis Dogoulis, Maxime Cordy, Nicos Maglaveras

Subjects: “…uncertainty quantification…”
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