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Uncertainty Quantification

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Showing 651–700 of 2366 papers

TitleStatusHype
Bayesian Joint Model of Multi-Sensor and Failure Event Data for Multi-Mode Failure Prediction—0
An Ensemble-Based Deep Framework for Estimating Thermo-Chemical State Variables from Flamelet Generated Manifolds—0
Deep Convolutional Architectures for Extrapolative Forecast in Time-dependent Flow Problems—0
Bayesian multi--dipole localization and uncertainty quantification from simultaneous EEG and MEG recordings—0
Efficient Medical Image Restoration via Reliability Guided Learning in Frequency Domain—0
A data-driven model order reduction approach for Stokes flow through random porous media—0
Deep interpretable ensembles—0
Efficient Multi-task Uncertainties for Joint Semantic Segmentation and Monocular Depth Estimation—0
Deep Latent Force Models: ODE-based Process Convolutions for Bayesian Deep Learning—0
Deep Learning Aided Laplace Based Bayesian Inference for Epidemiological Systems—0
Deep Learning: A Tutorial—0
Deep Learning-Based BMD Estimation from Radiographs with Conformal Uncertainty Quantification—0
Deep composition of tensor-trains using squared inverse Rosenblatt transports—0
Deep learning electromagnetic inversion with convolutional neural networks—0
Deep Learning for Ranking Response Surfaces with Applications to Optimal Stopping Problems—0
Screening for Diabetes Mellitus in the U.S. Population Using Neural Network Models and Complex Survey Designs—0
Deep Compositional Spatial Models—0
Bayesian Inference for Left-Truncated Log-Logistic Distributions for Time-to-event Data Analysis—0
Deep Capsule Encoder-Decoder Network for Surrogate Modeling and Uncertainty Quantification—0
Bayesian inference for data-efficient, explainable, and safe robotic motion planning: A review—0
Deep neural network surrogates for non-smooth quantities of interest in shape uncertainty quantification—0
Deep Neural Operator Enabled Digital Twin Modeling for Additive Manufacturing—0
DeepONet-Grid-UQ: A Trustworthy Deep Operator Framework for Predicting the Power Grid's Post-Fault Trajectories—0
Deep Operator Learning-based Surrogate Models with Uncertainty Quantification for Optimizing Internal Cooling Channel Rib Profiles—0
Efficient Line Search Method Based on Regression and Uncertainty Quantification—0
Deep priors for satellite image restoration with accurate uncertainties—0
Efficient Non-Parametric Uncertainty Quantification for Black-Box Large Language Models and Decision Planning—0
Deep Probability Segmentation: Are segmentation models probability estimators?—0
Deep State-Space Model for Predicting Cryptocurrency Price—0
DeeptDCS: Deep Learning-Based Estimation of Currents Induced During Transcranial Direct Current Stimulation—0
An out-of-distribution discriminator based on Bayesian neural network epistemic uncertainty—0
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification—0
Bayesian Imaging With Data-Driven Priors Encoded by Neural Networks: Theory, Methods, and Algorithms—0
Deformable Image Registration uncertainty quantification using deep learning for dose accumulation in adaptive proton therapy—0
Demonstration of machine-learning-enhanced Bayesian quantum state estimation—0
Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems—0
Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model—0
Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics—0
Density Uncertainty Quantification with NeRF-Ensembles: Impact of Data and Scene Constraints—0
Derivative-Informed Projected Neural Networks for High-Dimensional Parametric Maps Governed by PDEs—0
Bayesian Predictive Coding—0
A Novel Cluster Classify Regress Model Predictive Controller Formulation; CCR-MPC—0
A Deterministic Approximation to Neural SDEs—0
Adaptive Uncertainty Quantification for Generative AI—0
Deterministic Object Pose Confidence Region Estimation—0
Deterministic Trajectory Optimization through Probabilistic Optimal Control—0
Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability—0
DiffHybrid-UQ: Uncertainty Quantification for Differentiable Hybrid Neural Modeling—0
Efficient gPC-based quantification of probabilistic robustness for systems in neuroscience—0
Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents—0
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