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Uncertainty Quantification

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Showing 1901–1950 of 2366 papers

TitleStatusHype
Robustness and Reliability When Training With Noisy Labels—0
Uncertainty-aware GAN with Adaptive Loss for Robust MRI Image Enhancement—0
An Uncertainty-aware Loss Function for Training Neural Networks with Calibrated Predictions—0
Residual Overfit Method of Exploration—0
Δ-UQ: Accurate Uncertainty Quantification via Anchor Marginalization—0
Hierarchical Gaussian Process Models for Regression Discontinuity/Kink under Sharp and Fuzzy Designs—0
Lagrangian Inference for Ranking Problems—0
Out-of-Distribution Detection for Medical Applications: Guidelines for Practical EvaluationCode0
Non-stationary Gaussian process discriminant analysis with variable selection for high-dimensional functional dataCode0
UNCERTAINTY QUANTIFICATION USING VARIATIONAL INFERENCE FOR BIOMEDICAL IMAGE SEGMENTATION—0
Provably Calibrated Regression Under Distribution Drift—0
Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?—0
Learning to Estimate Epistemic Uncertainty in Neural Networks—0
Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How—0
Function-Space Variational Inference for Deep Bayesian Classification—0
MURO: Deployment Constrained Reinforcement Learning with Model-based Uncertainty Regularized Batch Optimization—0
Distribution-Driven Disjoint Prediction Intervals for Deep Learning—0
Particle Based Stochastic Policy Optimization—0
DynG2G: An Efficient Stochastic Graph Embedding Method for Temporal GraphsCode0
Grassmannian diffusion maps based surrogate modeling via geometric harmonics—0
Bayesian deep learning of affordances from RGB images—0
A neural multilevel method for high-dimensional parametric PDEs—0
Uncertainty quantification in covid-19 spread: lockdown effects—0
Bayesian non-parametric non-negative matrix factorization for pattern identification in environmental mixtures—0
Remaining useful life prediction with uncertainty quantification: development of a highly accurate model for rotating machinery—0
Accurate Remaining Useful Life Prediction with Uncertainty Quantification: a Deep Learning and Nonstationary Gaussian Process Approach—0
A Physics inspired Functional Operator for Model Uncertainty Quantification in the RKHS—0
A Data-Driven Uncertainty Quantification Method for Stochastic Economic Dispatch—0
Assessments of epistemic uncertainty using Gaussian stochastic weight averaging for fluid-flow regression—0
Machine-Learned HASDM Model with Uncertainty Quantification—0
Beyond Glass-Box Features: Uncertainty Quantification Enhanced Quality Estimation for Neural Machine Translation—0
DROMO: Distributionally Robust Offline Model-based Policy Optimization—0
Uncertainty Quantification in Medical Image Segmentation with Multi-decoder U-Net—0
A framework for benchmarking uncertainty in deep regression—0
Uncertainty Quantification and Experimental Design for Large-Scale Linear Inverse Problems under Gaussian Process Priors—0
AdjointNet: Constraining machine learning models with physics-based codes—0
Stochastic Neural Radiance Fields: Quantifying Uncertainty in Implicit 3D Representations—0
Deep Learning with Uncertainty Quantification for Predicting the Segmentation Dice Coefficient of Prostate Cancer Biopsy Images—0
Wasserstein Generative Adversarial Uncertainty Quantification in Physics-Informed Neural NetworksCode0
Uncertainty quantification for multiclass data description—0
Physics-Informed Deep Learning: A Promising Technique for System Reliability Assessment—0
MCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image ClassificationCode0
Uncertainty Quantification of the 4th kind; optimal posterior accuracy-uncertainty tradeoff with the minimum enclosing ballCode0
Teaching Uncertainty Quantification in Machine Learning through Use Cases—0
Neural density estimation and uncertainty quantification for laser induced breakdown spectroscopy spectra—0
Uncertainty quantification for industrial design using dictionaries of reduced order models—0
A variational Bayesian spatial interaction model for estimating revenue and demand at business facilities—0
Out-of-Domain Generalization from a Single Source: An Uncertainty Quantification Approach—0
Statistical Analysis of Wasserstein Distributionally Robust Estimators—0
Accelerating Markov Random Field Inference with Uncertainty Quantification—0
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