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Uncertainty Quantification

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Showing 1701–1750 of 2366 papers

TitleStatusHype
A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods—0
Are vision language models robust to uncertain inputs?—0
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods—0
A Rigorous Uncertainty-Aware Quantification Framework Is Essential for Reproducible and Replicable Machine Learning Workflows—0
A Risk-Aware Adaptive Robust MPC with Learned Uncertainty Quantification—0
A robustness measure for singular point and index estimation in discretized orientation and vector fields—0
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems—0
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness—0
A Soft Sensor Method with Uncertainty-Awareness and Self-Explanation Based on Large Language Models Enhanced by Domain Knowledge Retrieval—0
α-OCC: Uncertainty-Aware Camera-based 3D Semantic Occupancy Prediction—0
Assessment of DeepONet for reliability analysis of stochastic nonlinear dynamical systems—0
Assessment of Prediction Intervals Using Uncertainty Characteristics Curves—0
Assessment of Uncertainty Quantification in Universal Differential Equations—0
Assessments of epistemic uncertainty using Gaussian stochastic weight averaging for fluid-flow regression—0
Assumption-free fidelity bounds for hardware noise characterization—0
A Staged Approach using Machine Learning and Uncertainty Quantification to Predict the Risk of Hip Fracture—0
A Staged Deep Learning Approach to Spatial Refinement in 3D Temporal Atmospheric Transport—0
A Statistical Machine Learning Approach for Adapting Reduced-Order Models using Projected Gaussian Process—0
A Strategy for Adaptive Sampling of Multi-fidelity Gaussian Process to Reduce Predictive Uncertainty—0
A Structured Review of Literature on Uncertainty in Machine Learning & Deep Learning—0
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems—0
A Survey on Uncertainty Quantification Methods for Deep Learning—0
A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions—0
A Survey on Uncertainty Toolkits for Deep Learning—0
Asymmetric Duos: Sidekicks Improve Uncertainty—0
A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors—0
Asymptotic normality and confidence intervals for derivatives of 2-layers neural network in the random features model—0
Asymptotic Theory of Eigenvectors for Latent Embeddings with Generalized Laplacian Matrices—0
A Systematic Computational Framework for Practical Identifiability Analysis in Mathematical Models Arising from Biology—0
A Taylor Series Approach to Correction of Input Errors in Gaussian Process Regression—0
A Thermo-Electro-Mechanical Model for Long-Term Reliability of Aging Transmission Lines—0
AUGMENTED POLICY GRADIENT METHODS FOR EFFICIENT REINFORCEMENT LEARNING—0
AUGUR, A flexible and efficient optimization algorithm for identification of optimal adsorption sites—0
A Unified Bayesian Framework for Pricing Catastrophe Bond Derivatives—0
A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian Processes—0
AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification—0
Automated cross-sectional view selection in CT angiography of aortic dissections with uncertainty awareness and retrospective clinical annotations—0
Automated Learning of Interpretable Models with Quantified Uncertainty—0
Automatic AI controller that can drive with confidence: steering vehicle with uncertainty knowledge—0
Autonomous synthesis of metastable materials—0
AutoPQ: Automating Quantile estimation from Point forecasts in the context of sustainability—0
Auto-weighted Bayesian Physics-Informed Neural Networks and robust estimations for multitask inverse problems in pore-scale imaging of dissolution—0
A variational Bayesian spatial interaction model for estimating revenue and demand at business facilities—0
A Variational Inference Approach to Inverse Problems with Gamma Hyperpriors—0
A view on model misspecification in uncertainty quantification—0
Information-Geometric Barycenters for Bayesian Federated Learning—0
BARK: A Fully Bayesian Tree Kernel for Black-box Optimization—0
BARNN: A Bayesian Autoregressive and Recurrent Neural Network—0
Barrier Certificates for Unknown Systems with Latent States and Polynomial Dynamics using Bayesian Inference—0
Batch-Ensemble Stochastic Neural Networks for Out-of-Distribution Detection—0
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