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Uncertainty Quantification

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Showing 2051–2100 of 2366 papers

TitleStatusHype
Parameter inference in a computational model of hemodynamics in pulmonary hypertension—0
Bayesian neural networks for weak solution of PDEs with uncertainty quantification—0
Scaling Up Bayesian Uncertainty Quantification for Inverse Problems using Deep Neural Networks—0
Meta-Learning Bayesian Neural Network Priors Based on PAC-Bayesian Theory—0
Conditional Coverage Estimation for High-quality Prediction Intervals—0
DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation—0
Variational Deterministic Uncertainty Quantification—0
Bayesian Learning to Optimize: Quantifying the Optimizer Uncertainty—0
An Algorithm for Sensor Data Uncertainty Quantification—0
An Active Learning Method for Diabetic Retinopathy Classification with Uncertainty Quantification—0
Wasserstein DropoutCode0
Probabilistic Iterative Methods for Linear Systems—0
Uncertainty Bounds for Multivariate Machine Learning Predictions on High-Strain Brittle Fracture—0
Objective Evaluation of Deep Uncertainty Predictions for COVID-19 Detection—0
Alternating linear scheme in a Bayesian framework for low-rank tensor approximation—0
Multi-fidelity Bayesian Neural Networks: Algorithms and Applications—0
Uncertainty Quantification in Case of Imperfect Models: A Review—0
Active Learning for Deep Gaussian Process SurrogatesCode0
NP-ODE: Neural Process Aided Ordinary Differential Equations for Uncertainty Quantification of Finite Element AnalysisCode0
Asymptotic normality and confidence intervals for derivatives of 2-layers neural network in the random features model—0
Non-reversible Gaussian processes for identifying latent dynamical structure in neural data—0
Derivative-Informed Projected Neural Networks for High-Dimensional Parametric Maps Governed by PDEs—0
A Backward SDE Method for Uncertainty Quantification in Deep Learning—0
Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval—0
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs—0
Application of Deep Learning-based Interpolation Methods to Nearshore Bathymetry—0
Theory-guided Auto-Encoder for Surrogate Construction and Inverse Modeling—0
Fast Uncertainty Quantification for Deep Object Pose Estimation—0
Denoising Score-Matching for Uncertainty Quantification in Inverse ProblemsCode0
Efficient Variational Inference for Sparse Deep Learning with Theoretical GuaranteeCode0
Efficient Data Association and Uncertainty Quantification for Multi-Object Tracking—0
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges—0
(f,Γ)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics—0
Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging—0
Uncertainty Quantification of Darcy Flow through Porous Media using Deep Gaussian Process—0
Uncertainty Quantification in Extreme Learning Machine: Analytical Developments, Variance Estimates and Confidence Intervals—0
Reweighting samples under covariate shift using a Wasserstein distance criterion—0
KrigHedge: Gaussian Process Surrogates for Delta HedgingCode0
Emulator-based global sensitivity analysis for flow-like landslide run-out models—0
Physics-constrained Bayesian inference of state functions in classical density-functional theory—0
Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification ProceduresCode0
MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object DetectionCode0
Active Inference or Control as Inference? A Unifying View—0
A robustness measure for singular point and index estimation in discretized orientation and vector fields—0
Metrics for Benchmarking and Uncertainty Quantification: Quality, Applicability, and a Path to Best Practices for Machine Learning in Chemistry—0
BayesAdapter: Being Bayesian, Inexpensively and Robustly, via Bayesian Fine-tuning—0
Dynamic graph and polynomial chaos based models for contact tracing data analysis and optimal testing prescription—0
Automatic selection of basis-adaptive sparse polynomial chaos expansions for engineering applications—0
Improved Trainable Calibration Method for Neural Networks on Medical Imaging Classification—0
Mutual Information for Explainable Deep Learning of Multiscale Systems—0
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