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Uncertainty Quantification

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Showing 651–700 of 2366 papers

TitleStatusHype
Can Bayesian Neural Networks Make Confident Predictions?—0
Are generative models fair? A study of racial bias in dermatological image generation—0
Enhancing Diagnostic in 3D COVID-19 Pneumonia CT-scans through Explainable Uncertainty Bayesian Quantification—0
Deep Operator Networks for Bayesian Parameter Estimation in PDEs—0
A recursive Bayesian neural network for constitutive modeling of sands under monotonic loading—0
Uncertainty-Aware Digital Twins: Robust Model Predictive Control using Time-Series Deep Quantile Learning—0
Scalable Bayesian Physics-Informed Kolmogorov-Arnold Networks—0
A Critical Synthesis of Uncertainty Quantification and Foundation Models in Monocular Depth Estimation—0
Testing Human-Hand Segmentation on In-Distribution and Out-of-Distribution Data in Human-Robot Interactions Using a Deep Ensemble Model—0
Compact Bayesian Neural Networks via pruned MCMC samplingCode0
Uncertainty-Aware Online Extrinsic Calibration: A Conformal Prediction Approach—0
Evidential Deep Learning for Uncertainty Quantification and Out-of-Distribution Detection in Jet Identification using Deep Neural NetworksCode0
Distilling Calibration via Conformalized Credal Inference—0
Probabilistic Skip Connections for Deterministic Uncertainty Quantification in Deep Neural Networks—0
Statistical Uncertainty Quantification for Aggregate Performance Metrics in Machine Learning Benchmarks—0
Geophysical inverse problems with measurement-guided diffusion models—0
A Soft Sensor Method with Uncertainty-Awareness and Self-Explanation Based on Large Language Models Enhanced by Domain Knowledge Retrieval—0
Low-Order Flow Reconstruction and Uncertainty Quantification in Disturbed Aerodynamics Using Sparse Pressure MeasurementsCode0
From Aleatoric to Epistemic: Exploring Uncertainty Quantification Techniques in Artificial Intelligence—0
A Systematic Computational Framework for Practical Identifiability Analysis in Mathematical Models Arising from Biology—0
Physics-informed Gaussian Processes for Safe Envelope ExpansionCode0
Marketing Mix Modeling in Lemonade—0
Bayesian Active Learning By Distribution DisagreementCode0
An AI-powered Bayesian generative modeling approach for causal inference in observational studies—0
Monty Hall and Optimized Conformal Prediction to Improve Decision-Making with LLMs—0
Uncertainty-Aware Out-of-Distribution Detection with Gaussian Processes—0
Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks—0
When the whole is greater than the sum of its parts: Scaling black-box inference to large data settings through divide-and-conquer—0
Conformal Risk Control for Pulmonary Nodule DetectionCode0
Uncertainty quantification for improving radiomic-based models in radiation pneumonitis prediction—0
Uncertainty Quantification in Stereo MatchingCode0
Condensed Stein Variational Gradient Descent for Uncertainty Quantification of Neural Networks—0
Uncertainty Quantification in Continual Open-World Learning—0
Variability Need Not Imply Error: The Case of Adequate but Semantically Distinct ResponsesCode0
Reliability analysis for non-deterministic limit-states using stochastic emulators—0
Uncertainty separation via ensemble quantile regression—0
Evidential Deep Learning for Probabilistic Modelling of Extreme Storm EventsCode0
Distribution-Free Uncertainty Quantification in Mechanical Ventilation Treatment: A Conformal Deep Q-Learning Framework—0
On the Role of Surrogates in Conformal Inference of Individual Causal EffectsCode0
Reliable Breast Cancer Molecular Subtype Prediction based on uncertainty-aware Bayesian Deep Learning by Mammography—0
Constructing Confidence Intervals for Average Treatment Effects from Multiple DatasetsCode0
Information-Geometric Barycenters for Bayesian Federated Learning—0
Integrating Generative and Physics-Based Models for Ptychographic Imaging with Uncertainty Quantification—0
A Staged Deep Learning Approach to Spatial Refinement in 3D Temporal Atmospheric Transport—0
CESAR: A Convolutional Echo State AutoencodeR for High-Resolution Wind ForecastingCode0
Prescribing Decision Conservativeness in Two-Stage Power Markets: A Distributionally Robust End-to-End Approach—0
Distribution free uncertainty quantification in neuroscience-inspired deep operators—0
Subspace tracking for online system identification—0
Beyond Reweighting: On the Predictive Role of Covariate Shift in Effect Generalization—0
Bayesian optimized deep ensemble for uncertainty quantification of deep neural networks: a system safety case study on sodium fast reactor thermal stratification modeling—0
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