Application of Recurrent Neural Networks in Uncertainty Analysis of Sheet Metal Forming by Cruz Daniel, Parreira Tomás, Marques Armando, Prates Pedro, Oliveira Marta, Neto Diogo, Santos Abel, Amaral Rui, Barbosa Manuel, Pereira André

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A Hybrid Dropout Method for High-Precision Seafloor Topography Reconstruction and Uncertainty Quantification by Xinye Cui, Houpu Li, Yanting Yu, Shaofeng Bian, Guojun Zhai

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Uncertainty assessment of electromagnetic exposure safety for human body with intracranial artery stent around EV-WPT based on K-GRU surrogate model by Jiaxin Liu, Kaifeng Zhao, Quanyi Yu, Hongwei Zhou, Tianhao Wang, Yaodan Chi

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Inverse Uncertainty Quantification in Material Parameter Calibration Using Probabilistic and Interval Approaches by Thomas Most

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Forecasting Chlorophyll-a in the Murray–Darling Basin Using Remote Sensing by Ming Li, Klaus Joehnk, Peter Toscas, Luis Riera Garcia, Huidong Jin, Tapas K. Biswas

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Implementation of real-time incremental learning for ensemble hybrid model prediction in pilot scale bubble column aeration by Peter Jul-Rasmussen, Mads Stevnsborg, Xiaodong Liang, Jakob Kjøbsted Huusom

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Development of deep learning models for high-resolution exposome mapping and health impact assessment by Lan Luan, Zhu Daoyu

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Uncertainty quantification in modeling HIV viral mechanics by H. T. Banks, Robert Baraldi, Karissa Cross, Kevin Flores, Christina McChesney, Laura Poag, Emma Thorpe

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Systematic study of the propagation of uncertainties to transfer observables by C. Hebborn, C. Hebborn, C. Hebborn, F. M. Nunes, F. M. Nunes

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Bayesian Deep Learning Meets Self-Attention: A Risk-Aware Approach to Advertisement Optimization by Arti Jha, Ashutosh Bhatia, Kamlesh Tiwari

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Machine learning and uncertainty quantification to track and monitor natural frequencies in vibration-based SHM applied to offshore wind turbines by Maximillian Weil, Carlos Sastre Jurado, Wout Weijtjens, Christof Devriendt

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Improving the Predictability of the Madden‐Julian Oscillation at Subseasonal Scales With Gaussian Process Models by Haoyuan Chen, Emil Constantinescu, Vishwas Rao, Cristiana Stan

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Uncertainty quantification with Bayesian higher order ReLU-KANs by J Giroux, C Fanelli

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Multi-Sensor Temporal Fusion Transformer for Stock Performance Prediction: An Adaptive Sharpe Ratio Approach by Jingyun Yang, Pan Li, Yiwen Cui, Xu Han, Mengjie Zhou

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Machine Learning Techniques for Uncertainty Estimation in Dynamic Aperture Prediction by Carlo Emilio Montanari, Robert B. Appleby, Davide Di Croce, Massimo Giovannozzi, Tatiana Pieloni, Stefano Redaelli, Frederik F. Van der Veken

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GOMFuNet: A Geometric Orthogonal Multimodal Fusion Network for Enhanced Prediction Reliability by Yi Guo, Rui Zhong

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Evidential deep learning for uncertainty quantification and out-of-distribution detection in jet identification using deep neural networks by Ayush Khot, Xiwei Wang, Avik Roy, Volodymyr Kindratenko, Mark S Neubauer

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Introducing µGUIDE for quantitative imaging via generalized uncertainty-driven inference using deep learning by Maëliss Jallais, Marco Palombo

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Uncertainty-Guided Prediction Horizon of Phase-Resolved Ocean Wave Forecasting Under Data Sparsity: Experimental and Numerical Evaluation by Yuksel Rudy Alkarem, Kimberly Huguenard, Richard W. Kimball, Stephan T. Grilli

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An explainable AI-based framework for predicting and optimizing blast-induced ground vibrations in surface mining by Charan Kumar Ala, Zefree Lazarus Mayaluri, Aman Kaushik, Nikhat Parveen, Surabhi Saxena, Abu Taha Zamani, Debendra Muduli

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