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Uncertainty Quantification

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Showing 551–600 of 2366 papers

TitleStatusHype
Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks—0
An uncertainty-aware Digital Shadow for underground multimodal CO2 storage monitoring—0
Demonstration of machine-learning-enhanced Bayesian quantum state estimation—0
BayesIMP: Uncertainty Quantification for Causal Data Fusion—0
An Uncertainty-Aware Deep Learning Framework for Defect Detection in Casting Products—0
A Deep Learning Approach to Multi-Fiber Parameter Estimation and Uncertainty Quantification in Diffusion MRI—0
Density-aware NeRF Ensembles: Quantifying Predictive Uncertainty in Neural Radiance Fields—0
Density Uncertainty Quantification with NeRF-Ensembles: Impact of Data and Scene Constraints—0
Bayesian Uncertainty Quantification for Anaerobic Digestion models—0
Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval—0
A Deep Learning Approach to Dst Index Prediction—0
Bayesian subset selection and variable importance for interpretable prediction and classification—0
Antithetic Noise in Diffusion Models—0
A Bayesian Perspective on Uncertainty Quantification for Estimated Graph Signals—0
Bayesian Spike Train Inference via Non-Local Priors—0
Bayesian Sparse Regression for Mixed Multi-Responses with Application to Runtime Metrics Prediction in Fog Manufacturing—0
An Overview of Uncertainty Quantification Methods for Infinite Neural Networks—0
Bayesian semi-supervised learning for uncertainty-calibrated prediction of molecular properties and active learning—0
Bayesian SegNet for Semantic Segmentation with Improved Interpretation of Microstructural Evolution During Irradiation of Materials—0
An Overview of Large Language Models for Statisticians—0
A Deep Learning approach for parametrized and time dependent Partial Differential Equations using Dimensionality Reduction and Neural ODEs—0
Deformable Image Registration uncertainty quantification using deep learning for dose accumulation in adaptive proton therapy—0
Derivative-Informed Projected Neural Networks for High-Dimensional Parametric Maps Governed by PDEs—0
Dimensionality reduction can be used as a surrogate model for high-dimensional forward uncertainty quantification—0
Incremental Value and Interpretability of Radiomics Features of Both Lung and Epicardial Adipose Tissue for Detecting the Severity of COVID-19 Infection—0
Bayesian Recurrent Neural Network Models for Forecasting and Quantifying Uncertainty in Spatial-Temporal Data—0
Deep priors for satellite image restoration with accurate uncertainties—0
Bayesian Quantile Regression with Subset Selection: A Decision Analysis Perspective—0
A Novel Deep Learning Approach for Emulating Computationally Expensive Postfire Debris Flows—0
Uncertainty quantification of molecular property prediction using Bayesian neural network models—0
Bayesian Probabilistic Matrix Factorization—0
Bayesian Predictive Coding—0
A Novel Cluster Classify Regress Model Predictive Controller Formulation; CCR-MPC—0
Bayesian Physics-informed Neural Networks for System Identification of Inverter-dominated Power Systems—0
A Novel A.I Enhanced Reservoir Characterization with a Combined Mixture of Experts -- NVIDIA Modulus based Physics Informed Neural Operator Forward Model—0
A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglement—0
Deep Probability Segmentation: Are segmentation models probability estimators?—0
Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems—0
Bayesian Physics-Informed Extreme Learning Machine for Forward and Inverse PDE Problems with Noisy Data—0
A novel active learning-based Gaussian process metamodelling strategy for estimating the full probability distribution in forward UQ analysis—0
An out-of-distribution discriminator based on Bayesian neural network epistemic uncertainty—0
Bayesian Over-the-Air FedAvg via Channel Driven Stochastic Gradient Langevin Dynamics—0
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification—0
Deep Operator Learning-based Surrogate Models with Uncertainty Quantification for Optimizing Internal Cooling Channel Rib Profiles—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
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
DeepONet-Grid-UQ: A Trustworthy Deep Operator Framework for Predicting the Power Grid's Post-Fault Trajectories—0
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