Results 51 to 60 of about 7,687 (182)
Predicting Performance of Hall Effect Ion Source Using Machine Learning
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +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
Advanced Intelligent Systems, EarlyView.Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez +4 more
wiley +1 more source
Context-Aware Sensor Uncertainty Estimation for Autonomous Vehicles
Vehicles, 2021 Sensor uncertainty significantly affects the performance of autonomous vehicles (AVs). Sensor uncertainty is predominantly linked to sensor specifications, and because sensor behaviors change dynamically, the machine learning approach is not suitable for
Mohammed Alharbi, Hassan A. Karimi
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Chemistry – A European Journal, EarlyView.Machine‐learning potentials are increasingly taking on the exploratory tasks of homogeneous catalysis, enabling rapid conformer sampling and reaction‐space mapping. However, when selectivity depends on subtle electronic effects, electronic‐structure methods remain essential.
Maxime Ferrer +3 more
wiley +1 more source
Time's Arrow, December 8, 1995 [PDF]
, 1995 This is the concert program of the Time's Arrow performance on Friday, December 8, 1995 at 8:00 p.m., at the Tsai Performance Center, 685 Commonwealth Avenue, Boston, Massachusetts.
School of Music, Boston University
core
Rethinking Aleatoric and Epistemic Uncertainty
Published at ICML ...
Bickford Smith, F +5 more
openaire +3 more sources
Data driven drift correction for complex optical systems
Journal of Synchrotron Radiation, EarlyView.Time varying Bayesian optimization as a data driven approach for robust drift correction is outlined, and its application for a split and delay x‐ray optical system is illustrated.To exploit the thousand‐fold increase in spectral brightness of modern light sources, increasingly intricate experiments are being conducted that demand extremely precise ...
Aashwin Mishra +6 more
wiley +1 more source
Field-Level Uncertainty Quantification for AI-Based Ship Hull Surface Pressure Prediction
Journal of Marine Science and EngineeringThis study investigates uncertainty quantification for field-level ship hull surface pressure predictions using a U-Net-based data-driven model. A speed-conditioned U-Net is trained on a large CFD dataset covering multiple ship types and velocity ...
Jeongbeom Seo, Inwon Lee
doaj +1 more source
Frontiers in Medicine, 2022 Lung adenocarcinoma (LUAD) is the most common type of lung cancer. Accurate identification of lymph node (LN) involvement in patients with LUAD is crucial for prognosis and making decisions of the treatment strategy. CT imaging has been used as a tool to
Qianli Ma +6 more
doaj +1 more source