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Uncertainty Quantification

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Showing 1526–1550 of 2366 papers

TitleStatusHype
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review—0
Adaptive Modeling of Uncertainties for Traffic Forecasting—0
Application of probabilistic modeling and automated machine learning framework for high-dimensional stress field—0
Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review—0
Validation of uncertainty quantification metrics: a primer based on the consistency and adaptivity conceptsCode0
Efficient Bayesian Physics Informed Neural Networks for Inverse Problems via Ensemble Kalman Inversion—0
Lifelong Machine Learning Potentials—0
Uncertainty quantification in neural network classifiers -- a local linear approach—0
HappyMap: A Generalized Multi-calibration Method—0
Uncertainty Quantification of Spatiotemporal Travel Demand with Probabilistic Graph Neural NetworksCode0
Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification—0
Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis—0
Expectation consistency for calibration of neural networksCode0
Wasserstein Actor-Critic: Directed Exploration via Optimism for Continuous-Actions Control—0
Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing SymmetriesCode0
Multi-Head Multi-Loss Model CalibrationCode0
Toward Robust Uncertainty Estimation with Random Activation FunctionsCode0
Bayesian Kernelized Tensor Factorization as Surrogate for Bayesian Optimization—0
Unsupervised Domain Adaptation for Low-dose CT Reconstruction via Bayesian Uncertainty AlignmentCode0
A Survey on Uncertainty Quantification Methods for Deep Learning—0
Calibrated Regression Against An Adversary Without Regret—0
Learning Mixture Structure on Multi-Source Time Series for Probabilistic Forecasting—0
Improved uncertainty quantification for neural networks with Bayesian last layerCode0
Data-driven reduced-order modelling for blood flow simulations with geometry-informed snapshotsCode0
Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles—0
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