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Uncertainty Quantification

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Showing 301–350 of 2366 papers

TitleStatusHype
A Learning- and Scenario-based MPC Design for Nonlinear Systems in LPV Framework with Safety and Stability Guarantees—0
A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian Processes—0
A Kernel Framework to Quantify a Model's Local Predictive Uncertainty under Data Distributional Shifts—0
Accessible, At-Home Detection of Parkinson's Disease via Multi-task Video Analysis—0
A Unified Bayesian Framework for Pricing Catastrophe Bond Derivatives—0
AUGUR, A flexible and efficient optimization algorithm for identification of optimal adsorption sites—0
Active search for Bifurcations—0
AUGMENTED POLICY GRADIENT METHODS FOR EFFICIENT REINFORCEMENT LEARNING—0
A Thermo-Electro-Mechanical Model for Long-Term Reliability of Aging Transmission Lines—0
A Kernel-Based Approach for Modelling Gaussian Processes with Functional Information—0
Structure and asymptotic preserving deep neural surrogates for uncertainty quantification in multiscale kinetic equations—0
Characterising User Transfer Amid Industrial Resource Variation: A Bayesian Nonparametric Approach—0
A Taylor Series Approach to Correction of Input Errors in Gaussian Process Regression—0
A Systematic Computational Framework for Practical Identifiability Analysis in Mathematical Models Arising from Biology—0
AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble—0
Asymptotic Theory of Eigenvectors for Latent Embeddings with Generalized Laplacian Matrices—0
Asymptotic normality and confidence intervals for derivatives of 2-layers neural network in the random features model—0
AI-Powered Bayesian Inference—0
Active operator learning with predictive uncertainty quantification for partial differential equations—0
A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors—0
Asymmetric Duos: Sidekicks Improve Uncertainty—0
AI enhanced data assimilation and uncertainty quantification applied to Geological Carbon Storage—0
A Survey on Uncertainty Toolkits for Deep Learning—0
A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions—0
AI-Assisted Decision-Making for Clinical Assessment of Auto-Segmented Contour Quality—0
Active Learning with Multifidelity Modeling for Efficient Rare Event Simulation—0
Acceleration of stochastic gradient descent with momentum by averaging: finite-sample rates and asymptotic normality—0
Clarifying Trust of Materials Property Predictions using Neural Networks with Distribution-Specific Uncertainty Quantification—0
A Survey on Uncertainty Quantification Methods for Deep Learning—0
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems—0
A Hybrid Feature Fusion Deep Learning Framework for Leukemia Cancer Detection in Microscopic Blood Sample Using Gated Recurrent Unit and Uncertainty Quantification—0
Accelerating Markov Random Field Inference with Uncertainty Quantification—0
A Hybrid Deep Neural Operator/Finite Element Method for Ice-Sheet Modeling—0
Exploiting the Asymmetric Uncertainty Structure of Pre-trained VLMs on the Unit Hypersphere—0
Centroid Approximation for Bootstrap: Improving Particle Quality at Inference—0
A Structured Review of Literature on Uncertainty in Machine Learning & Deep Learning—0
A Strategy for Adaptive Sampling of Multi-fidelity Gaussian Process to Reduce Predictive Uncertainty—0
A hybrid data driven-physics constrained Gaussian process regression framework with deep kernel for uncertainty quantification—0
A Statistical Machine Learning Approach for Adapting Reduced-Order Models using Projected Gaussian Process—0
A Staged Deep Learning Approach to Spatial Refinement in 3D Temporal Atmospheric Transport—0
Active Inference or Control as Inference? A Unifying View—0
Certified and fast computations with shallow covariance kernels—0
A Staged Approach using Machine Learning and Uncertainty Quantification to Predict the Risk of Hip Fracture—0
Assumption-free fidelity bounds for hardware noise characterization—0
Assessments of epistemic uncertainty using Gaussian stochastic weight averaging for fluid-flow regression—0
Assessment of Uncertainty Quantification in Universal Differential Equations—0
Agreeing to Stop: Reliable Latency-Adaptive Decision Making via Ensembles of Spiking Neural Networks—0
Accelerating Ensemble Error Bar Prediction with Single Models Fits—0
Assessment of Prediction Intervals Using Uncertainty Characteristics Curves—0
Assessment of DeepONet for reliability analysis of stochastic nonlinear dynamical systems—0
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