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Uncertainty Quantification

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Showing 2001–2025 of 2366 papers

TitleStatusHype
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
Deep Operator Networks for Bayesian Parameter Estimation in PDEs—0
Deep priors for satellite image restoration with accurate uncertainties—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
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
Density-aware NeRF Ensembles: Quantifying Predictive Uncertainty in Neural Radiance Fields—0
Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks—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
A Deterministic Approximation to Neural SDEs—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
Dimensionality reduction can be used as a surrogate model for high-dimensional forward uncertainty quantification—0
Dimension-Free Average Treatment Effect Inference with Deep Neural Networks—0
Directed Cyclic Graph for Causal Discovery from Multivariate Functional Data—0
Direct segmentation of brain white matter tracts in diffusion MRI—0
Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks—0
Discovery of Probabilistic Dirichlet-to-Neumann Maps on Graphs—0
Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods—0
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