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Uncertainty Quantification

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Showing 951–1000 of 2366 papers

TitleStatusHype
Analytical results for uncertainty propagation through trained machine learning regression models—0
From Physics to Foundation Models: A Review of AI-Driven Quantitative Remote Sensing Inversion—0
From PINNs to PIKANs: Recent Advances in Physics-Informed Machine Learning—0
From predictions to confidence intervals: an empirical study of conformal prediction methods for in-context learning—0
From Robustness to Improved Generalization and Calibration in Pre-trained Language Models—0
Accurate Prediction and Uncertainty Estimation using Decoupled Prediction Interval Networks—0
Conditional Distribution Quantization in Machine Learning—0
A Survey on Uncertainty Quantification Methods for Deep Learning—0
Data-driven multi-agent modelling of calcium interactions in cell culture: PINN vs Regularized Least-squares—0
Data-Driven Model Selections of Second-Order Particle Dynamics via Integrating Gaussian Processes with Low-Dimensional Interacting Structures—0
Bayesian Dynamical System Identification With Unified Sparsity Priors And Model Uncertainty—0
Functional Bayesian Neural Networks for Model Uncertainty Quantification—0
Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs—0
Functional PCA and Deep Neural Networks-based Bayesian Inverse Uncertainty Quantification with Transient Experimental Data—0
Functional SDE approximation inspired by a deep operator network architecture—0
Functional Stochastic Gradient MCMC for Bayesian Neural Networks—0
Data-driven method for real-time prediction and uncertainty quantification of fatigue failure under stochastic loading using artificial neural networks and Gaussian process regression—0
Function Space Bayesian Pseudocoreset for Bayesian Neural Networks—0
Asymmetric Duos: Sidekicks Improve Uncertainty—0
Function-Space Regularization for Deep Bayesian Classification—0
Function-Space Variational Inference for Deep Bayesian Classification—0
Future-Proofing Medical Imaging with Privacy-Preserving Federated Learning and Uncertainty Quantification: A Review—0
Fuzzy finite element model updating using metaheuristic optimization algorithms—0
Data-Driven Gradient Optimization for Field Emission Management in a Superconducting Radio-Frequency Linac—0
Game-Theoretic Defenses for Robust Conformal Prediction Against Adversarial Attacks in Medical Imaging—0
Gamifying optimization: a Wasserstein distance-based analysis of human search—0
Bayesian Deep Neural Networks for Supervised Learning of Single-View Depth—0
Conditional Variational Autoencoder for Learned Image Reconstruction—0
Analysis of Diagnostics (Part II): Prevalence, Linear Independence, and Unsupervised Learning—0
Gaussian Differential Private Bootstrap by Subsampling—0
Gaussian Experts Selection using Graphical Models—0
Gaussian Measures Conditioned on Nonlinear Observations: Consistency, MAP Estimators, and Simulation—0
Gaussian processes for dynamics learning in model predictive control—0
Gaussian Processes in Power Systems: Techniques, Applications, and Future Works—0
Simultaneous Reconstruction and Uncertainty Quantification for Tomography—0
Gaussian process interpolation with conformal prediction: methods and comparative analysis—0
Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior—0
Confident magnitude-based neural network pruning—0
Gaussian process surrogate model to approximate power grid simulators -- An application to the certification of a congestion management controller—0
Gaussian Process Upper Confidence Bounds in Distributed Point Target Tracking over Wireless Sensor Networks—0
Accurate Data-Driven Surrogates of Dynamical Systems for Forward Propagation of Uncertainty—0
Bayesian Deep Learning via Stochastic Gradient MCMC with a Stochastic Approximation Adaptation—0
Learning particle swarming models from data with Gaussian processes—0
General Intelligent Imaging and Uncertainty Quantification by Deterministic Diffusion Model—0
Generalized Bayesian Additive Regression Trees Models: Beyond Conditional Conjugacy—0
Generalized Uncertainty of Deep Neural Networks: Taxonomy and Applications—0
AUGMENTED POLICY GRADIENT METHODS FOR EFFICIENT REINFORCEMENT LEARNING—0
Generalizing Large Language Model Usability Across Resource-Constrained—0
Generalizing Machine Learning Evaluation through the Integration of Shannon Entropy and Rough Set Theory—0
Analysis, forecasting and system identification of a floating offshore wind turbine using dynamic mode decomposition—0
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