Results 71 to 80 of about 1,009,621 (180)

TrustSpec: Simulation‐Grounded Physics‐Driven Spectral Inversion With Uncertainty Quantification for SiC Epitaxial Thickness Metrology

Engineering Reports, Volume 8, Issue 10, October 2026.
TrustSpec reuses a single spectral digital twin both to train a deep ensemble and to verify each prediction via analysis‐by‐synthesis. A two‐channel trust plane automatically releases, reviews, or rejects every SiC epitaxial thickness reading, achieving 0.110 μm mean error with full out‐of‐distribution rejection in simulation.
Zijie Nie, Shunlin Yang, Qingjie Guo
wiley   +1 more source

Uncertainty-Aware Time Series Anomaly Detection

Future Internet
Traditional anomaly detection methods in time series data often struggle with inherent uncertainties like noise and missing values. Indeed, current approaches mostly focus on quantifying epistemic uncertainty and ignore data-dependent uncertainty ...
Paul Wiessner, Grigor Bezirganyan, Sana Sellami, Richard Chbeir, Hans-Joachim Bungartz   +4 more
doaj   +1 more source

Explainable uncertainty quantifications for deep learning-based molecular property prediction

Journal of Cheminformatics, 2023
Quantifying uncertainty in machine learning is important in new research areas with scarce high-quality data. In this work, we develop an explainable uncertainty quantification method for deep learning-based molecular property prediction. This method can
Chu-I Yang, Yi-Pei Li
doaj   +1 more source

Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty [PDF]

Information Sciences, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Robin Senge, Stefan Bösner, Krzysztof Dembczynski, Jörg Haasenritter, Oliver Hirsch, Norbert Donner-Banzhoff, Eyke Hüllermeier   +6 more
openaire   +3 more sources

Analytical Framework for System‐Level Fragility Surfaces of Reinforced Concrete Bridges Under Mainshock‐Aftershock Sequences

Earthquake Engineering &Structural Dynamics, Volume 55, Issue 13, Page 3264-3284, 25 October 2026.
ABSTRACT Conventional single intensity measure (IM) fragility approaches with simplified component dependency assumptions overlook the progressive damage accumulation and evolving inter‐component correlations that govern system behavior under mainshock‐aftershock (MSAS) loading.
Muhammad Rashid, Mayuko Nishio
wiley   +1 more source

Improved multi-objective decision-making in manufacturing processes through uncertainty quantification and robust pareto front modelling

Scientific Reports
Manufacturing processes often exhibit complex relationships between input parameters and output responses, posing challenges for optimization and decision-making.
Arne De Temmerman, Mathias Verbeke
doaj   +1 more source

Uncertainty in property valuation: aleatoric and epistemic challenges in the Nigerian real estate market

Acta Scientiarum Polonorum. Administratio Locorum
Motivation: Real estate markets, particularly in emerging economies such as Nigeria, are subject to significant uncertainties. These can be broadly categorized into aleatoric uncertainties, which arise from inherent market variability, and epistemic ...
Nonso Izuchukwu Ewurum, Njideka Maryclara Aguome, Cezary Kowalczyk, Ikechukwu William-Johnson Ozigbo, Jacek Kil   +4 more
doaj   +1 more source

Rheokinetic Study of Polycarbodiimide Formation From 4,4’‐MDI Using Rotational Viscometry—A Characterization of Gelation

Macromolecular Materials and Engineering, Volume 311, Issue 10, October 2026.
Temperature‐dependent rheokinetic analysis reveals how MDI solution evolves into a transparent polycarbodiimide gel. Rotational viscometry, isoviscosity mapping, and fractional‐order modeling quantify viscosity growth, gel‐time estimation, and apparent activation energy, providing a compact framework for understanding carbodiimide‐driven gelation in ...
Marcell Dániel Csécsi, Péter Tóth, László Farkas, Christa Fittschen, Milán Szőri, Béla Viskolcz   +5 more
wiley   +1 more source

An uncertainty-aware domain adaptive semantic segmentation framework

Autonomous Intelligent Systems
Semantic segmentation is significant to realize the scene understanding of autonomous driving. Due to the lack of annotated real-world data, the technology of domain adaptation is applied so that the model is trained on the synthetic data and inferred on
Huilin Yin, Pengyu Wang, Boyu Liu, Jun Yan   +3 more
doaj   +1 more source

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
openaire   +3 more sources