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Uncertainty Quantification

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Showing 1701–1750 of 2366 papers

TitleStatusHype
Scalable Uncertainty Quantification for Deep Operator Networks using Randomized PriorsCode1
NUQ: A Noise Metric for Diffusion MRI via Uncertainty Discrepancy Quantification—0
Bayesian Spillover Graphs for Dynamic NetworksCode0
MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for multiple uncertainty types and tasksCode1
Machine learning models predict calculation outcomes with the transferability necessary for computational catalysis—0
Bayesian adaptive and interpretable functional regression for exposure profilesCode0
Rule-based Evolutionary Bayesian LearningCode0
Bayesian autoencoders with uncertainty quantification: Towards trustworthy anomaly detection—0
On Monocular Depth Estimation and Uncertainty Quantification using Classification Approaches for Regression—0
AutoIP: A United Framework to Integrate Physics into Gaussian ProcessesCode1
Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement LearningCode1
UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed TomographyCode1
Off-Policy Confidence Interval Estimation with Confounded Markov Decision ProcessCode0
GAN-DUF: Hierarchical Deep Generative Models for Design Under Free-Form Geometric UncertaintyCode0
Stochastic Modeling of Inhomogeneities in the Aortic Wall and Uncertainty Quantification using a Bayesian Encoder-Decoder Surrogate—0
Generalized Bayesian Additive Regression Trees Models: Beyond Conditional Conjugacy—0
Accurate Prediction and Uncertainty Estimation using Decoupled Prediction Interval Networks—0
Highlighting Object Category Immunity for the Generalization of Human-Object Interaction DetectionCode0
DeepONet-Grid-UQ: A Trustworthy Deep Operator Framework for Predicting the Power Grid's Post-Fault Trajectories—0
Adaptive Conformal Predictions for Time SeriesCode1
Deep Ensembles Work, But Are They Necessary?Code0
Local approximation of operators—0
Deep Learning to advance the Eigenspace Perturbation Method for Turbulence Model Uncertainty Quantification—0
Mining the manifolds of deep generative models for multiple data-consistent solutions of ill-posed tomographic imaging problemsCode0
PCENet: High Dimensional Surrogate Modeling for Learning Uncertainty—0
Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in ImagingCode1
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems—0
Model Architecture Adaption for Bayesian Neural Networks—0
Multi-model Ensemble Analysis with Neural Network Gaussian Processes—0
Impact of Parameter Sparsity on Stochastic Gradient MCMC Methods for Bayesian Deep Learning—0
Nonparametric Uncertainty Quantification for Single Deterministic Neural NetworkCode1
Non-parametric Uncertainty Assessment in Deep-Learning Based Affine Image Registration—0
Deformable Image Registration uncertainty quantification using deep learning for dose accumulation in adaptive proton therapy—0
Uncertainty-aware Pseudo-label Selection for Positive-Unlabeled Learning—0
Assessment of DeepONet for reliability analysis of stochastic nonlinear dynamical systems—0
UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANsCode1
Counterfactual Plans under Distributional AmbiguityCode0
A Kernel-Based Approach for Modelling Gaussian Processes with Functional Information—0
Analytic Mutual Information in Bayesian Neural Networks—0
Spherical Poisson Point Process Intensity Function Modeling and Estimation with Measure TransportCode0
alpha-Deep Probabilistic Inference (alpha-DPI): efficient uncertainty quantification from exoplanet astrometry to black hole feature extractionCode1
WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for SuperresolutionCode1
Uncertainty Quantification in Scientific Machine Learning: Methods, Metrics, and ComparisonsCode2
Deep Capsule Encoder-Decoder Network for Surrogate Modeling and Uncertainty Quantification—0
Machine Learning Enhances Algorithms for Quantifying Non-Equilibrium Dynamics in Correlation Spectroscopy Experiments to Reach Frame-Rate-Limited Time Resolution—0
Better Uncertainty Quantification for Machine Translation Evaluation—0
Probabilistic Mass Mapping with Neural Score Estimation—0
A Kernel-Expanded Stochastic Neural NetworkCode0
An Overview of Uncertainty Quantification Methods for Infinite Neural Networks—0
Two Wrongs Can Make a Right: A Transfer Learning Approach for Chemical Discovery with Chemical Accuracy—0
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