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Uncertainty Quantification

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Showing 601–650 of 2366 papers

TitleStatusHype
A Note on Uncertainty Quantification for Maximum Likelihood Parameters Estimated with Heuristic Based Optimization Algorithms—0
Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI—0
Bayesian Numerical Methods for Nonlinear Partial Differential Equations—0
Alpha-VI DeepONet: A prior-robust variational Bayesian approach for enhancing DeepONets with uncertainty quantification—0
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables—0
DROMO: Distributionally Robust Offline Model-based Policy Optimization—0
Bayesian non-parametric non-negative matrix factorization for pattern identification in environmental mixtures—0
A Data-Driven Uncertainty Quantification Method for Stochastic Economic Dispatch—0
Bayesian neural networks for weak solution of PDEs with uncertainty quantification—0
Bayesian neural networks for predicting uncertainty in full-field material response—0
Anomaly Detection using Ensemble Classification and Evidence Theory—0
Do Bayesian imaging methods report trustworthy probabilities?—0
Bayesian neural networks and dimensionality reduction—0
Bayesian Neural Network Inference via Implicit Models and the Posterior Predictive Distribution—0
Anisotropic Hybrid Networks for liver tumor segmentation with uncertainty quantification—0
Bayesian Neural Hawkes Process for Event Uncertainty Prediction—0
A data-driven model order reduction approach for Stokes flow through random porous media—0
Achieving an Accurate Random Process Model for PV Power using Cheap Data: Leveraging the SDE and Public Weather Reports—0
Diverse Randomized Value Functions: A Provably Pessimistic Approach for Offline Reinforcement Learning—0
Bayesian multi--dipole localization and uncertainty quantification from simultaneous EEG and MEG recordings—0
A New PHO-rmula for Improved Performance of Semi-Structured Networks—0
A Chaotic Dynamical System that Paints—0
Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How—0
Bayesian meta learning for trustworthy uncertainty quantification—0
A data-driven epidemic model with social structure for understanding the COVID-19 infection on a heavily affected Italian Province—0
Uncertainty Quantification for Prior-Data Fitted Networks using Martingale Posteriors—0
A neural multilevel method for high-dimensional parametric PDEs—0
Bayesian Learning to Optimize: Quantifying the Optimizer Uncertainty—0
Distribution-free uncertainty quantification for classification under label shift—0
Bayesian learning of the optimal action-value function in a Markov decision process—0
An Ensemble Quadratic Echo State Network for Nonlinear Spatio-Temporal Forecasting—0
A data-centric weak supervised learning for highway traffic incident detection—0
Distribution free uncertainty quantification in neuroscience-inspired deep operators—0
Distribution-Free Uncertainty Quantification in Mechanical Ventilation Treatment: A Conformal Deep Q-Learning Framework—0
Do Large Language Models (Really) Need Statistical Foundations?—0
Dual-Channel Reliable Breast Ultrasound Image Classification Based on Explainable Attribution and Uncertainty Quantification—0
Efficient Epistemic Uncertainty Estimation in Cerebrovascular Segmentation—0
Deep Deterministic Uncertainty: A New Simple Baseline—0
Bayesian Kernelized Tensor Factorization as Surrogate for Bayesian Optimization—0
Deep Echo State Networks with Uncertainty Quantification for Spatio-Temporal Forecasting—0
Deep Ensemble as a Gaussian Process Approximate Posterior—0
Deep-Ensemble-Based Uncertainty Quantification in Spatiotemporal Graph Neural Networks for Traffic Forecasting—0
Deep Ensembles from a Bayesian Perspective—0
Deep Ensembles to Improve Uncertainty Quantification of Statistical Downscaling Models under Climate Change Conditions—0
Bayesian LSTM for indoor temperature modeling—0
Deep convolutional neural networks for uncertainty propagation in random fields—0
Deep Evidential Learning for Bayesian Quantile Regression—0
Deep Evidential Learning for Radiotherapy Dose Prediction—0
Bayesian Joint Model of Multi-Sensor and Failure Event Data for Multi-Mode Failure Prediction—0
An Ensemble-Based Deep Framework for Estimating Thermo-Chemical State Variables from Flamelet Generated Manifolds—0
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