Results 91 to 100 of about 3,934 (193)

Anonim, Przeciw Kosterom (Adversus aleatores)

Vox Patrum, 1983
tłumaczenie
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Aleatoric music generated by grammars

The goal of this thesis was to design a grammar that would allow for the generation of aleatoric music. Next the grammar would be used in a specific application.
Koch, Karel
core   +1 more source

Toward a New Flood Assessment Paradigm: From Exceedance Probabilities to the Expected Maximum Floods and Damages

Water Resources Research
To assess flood risks, we seek to estimate the probability distribution of the worst possible single‐event over a contiguous period of N years rather than the cumulative losses expected over a planning horizon.
E. Todini, P. Reggiani
doaj   +1 more source

CLEAR: Calibrated Learning for Epistemic and Aleatoric Risk

CoRR
Accurate uncertainty quantification is critical for reliable predictive modeling. Existing methods typically address either aleatoric uncertainty due to measurement noise or epistemic uncertainty resulting from limited data, but not both in a balanced manner.
Ilia Azizi, Juraj Bodik, Jakob Heiss, Bin Yu   +3 more
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Estimating Aleatoric Uncertainty in the Causal Treatment Effect

CoRR
Previous work on causal inference has primarily focused on averages and conditional averages of treatment effects, with significantly less attention on variability and uncertainty in individual treatment responses. In this paper, we introduce the variance of the treatment effect (VTE) and conditional variance of treatment effect (CVTE) as the natural ...
Liyuan Xu, Bijan Mazaheri
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MA-UQNet: A multi-modal uncertainty quantification neural network for remote sensing-based wheat aboveground biomass estimation

Artificial Intelligence in Agriculture
Accurate aboveground biomass estimation with quantified uncertainty is essential for precision agriculture, enabling risk-aware decision-making and strategic model improvement. Existing approaches predominantly provide point estimates without uncertainty
Qiang Wu, Jiao Wang, Yuke Du, Dingyi Hou, Xiaoyu Cao, Xiaochun Wang, Hao Yang, Guijun Yang, Xinming Ma, Jinpeng Cheng   +9 more
doaj   +1 more source

Estimating Epistemic and Aleatoric Uncertainty with a Single Model

Advances in Neural Information Processing Systems 37
Estimating and disentangling epistemic uncertainty, uncertainty that is reducible with more training data, and aleatoric uncertainty, uncertainty that is inherent to the task at hand, is critically important when applying machine learning to high-stakes applications such as medical imaging and weather forecasting.
Matthew Chan, Maria Molina, Chris Metzler   +2 more
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Epistemic and aleatoric uncertainty quantification in weather and climate models

Representing and quantifying uncertainty in physical parameterisations is a central challenge in weather and climate modelling, and approaches are often developed separately for different time‐scales.
Mansfield, Laura A., Christensen, Hannah M.   +1 more
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A Trustworthy Model With Uncertainty Management for Predicting Vascular Access Dysfunction in Hemodialysis Patients

IEEE Access
Vascular access dysfunction is a prevalent and critical complication among hemodialysis patients, particularly in Taiwan, which has the highest proportion of dialysis patients globally. Early diagnosis and effective management are essential for improving
Chia-Hsun Lin, Zheng Lin Chen, Chung-Kuan Wu, Tsen-Che Wu, Ching-Wen Ma   +4 more
doaj   +1 more source

Machine learning surrogate for charged particle beam dynamics with space charge based on a recurrent neural network with aleatoric uncertainty

Physical Review Accelerators and Beams
In this work, we develop a machine learning (ML) model with aleatoric uncertainty for the low energy beam transport (LEBT) region of the LANSCE linear accelerator in which we model the transport of a space-charge-dominated 750 keV proton beam through a ...
Cristina Garcia-Cardona, Alexander Scheinker   +1 more
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