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Uncertainty Quantification

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Showing 1551–1600 of 2366 papers

TitleStatusHype
Credal Bayesian Deep Learning—0
Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions—0
Bayesian Quantification with Black-Box EstimatorsCode0
Entity Aware Modelling: A Survey—0
B-BACN: Bayesian Boundary-Aware Convolutional Network for Crack Characterization—0
Fixing Overconfidence in Dynamic Neural NetworksCode0
Event Temporal Relation Extraction with Bayesian Translational Model—0
On Fairness and Stability: Is Estimator Variance a Friend or a Foe?—0
IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning—0
Clarifying Trust of Materials Property Predictions using Neural Networks with Distribution-Specific Uncertainty Quantification—0
Variational Inference on the Final-Layer Output of Neural NetworksCode0
Generalized Uncertainty of Deep Neural Networks: Taxonomy and Applications—0
Randomized prior wavelet neural operator for uncertainty quantification—0
Physics Constrained Motion Prediction with Uncertainty Quantification—0
Benchmarking Probabilistic Deep Learning Methods for License Plate RecognitionCode0
Hierarchical shrinkage Gaussian processes: applications to computer code emulation and dynamical system recovery—0
Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference—0
Convergence of uncertainty estimates in Ensemble and Bayesian sparse model discovery—0
On Second-Order Scoring Rules for Epistemic Uncertainty Quantification—0
Incremental Value and Interpretability of Radiomics Features of Both Lung and Epicardial Adipose Tissue for Detecting the Severity of COVID-19 Infection—0
Combinatorial Inference on the Optimal Assortment in Multinomial Logit Models—0
From Classification Accuracy to Proper Scoring Rules: Elicitability of Probabilistic Top List Predictions—0
Conformal Prediction for Trustworthy Detection of Railway Signals—0
Neural-Symbolic Inference for Robust Autoregressive Graph Parsing via Compositional Uncertainty Quantification—0
A Hybrid Deep Neural Operator/Finite Element Method for Ice-Sheet Modeling—0
Adaptive Probabilistic Forecasting of Electricity (Net-)Load—0
Semiparametric inference using fractional posteriors—0
Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics—0
Uncertainty Quantification for Local Model Explanations Without Model AccessCode0
A Rigorous Uncertainty-Aware Quantification Framework Is Essential for Reproducible and Replicable Machine Learning Workflows—0
Constraining cosmological parameters from N-body simulations with Variational Bayesian Neural Networks—0
Deep Injective Prior for Inverse ScatteringCode0
L-HYDRA: Multi-Head Physics-Informed Neural NetworksCode0
Deep Deterministic Uncertainty: A New Simple Baseline—0
Non-intrusive surrogate modelling using sparse random features with applications in crashworthiness analysis—0
Posterior sampling with CNN-based, Plug-and-Play regularization with applications to Post-Stack Seismic Inversion—0
A Learning-Based Optimal Uncertainty Quantification Method and Its Application to Ballistic Impact Problems—0
Improving Uncertainty Quantification of Variance Networks by Tree-Structured LearningCode0
Anomaly Detection using Ensemble Classification and Evidence Theory—0
Parameter Inference based on Gaussian Processes Informed by Nonlinear Partial Differential EquationsCode0
Uncertainty Quantification of MLE for Entity Ranking with Covariates—0
Estimating and Assessing Differential Equation Models with Time-Course Data—0
Demonstration of machine-learning-enhanced Bayesian quantum state estimation—0
Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and Pitfalls—0
Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks—0
Generative structured normalizing flow Gaussian processes applied to spectroscopic data—0
Uncertainty Quantification for Deep Neural Networks: An Empirical Comparison and Usage Guidelines—0
Reliable Multimodal Trajectory Prediction via Error Aligned Uncertainty Optimization—0
Uncertainty Estimation in Deep Speech Enhancement Using Complex Gaussian Mixture Models—0
Enhanced prediction accuracy with uncertainty quantification in monitoring CO2 sequestration using convolutional neural networks—0
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