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Uncertainty Quantification

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Showing 1451–1500 of 2366 papers

TitleStatusHype
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
Fully Nonparametric Bayesian Additive Regression Trees—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
Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions—0
Function Space Bayesian Pseudocoreset for Bayesian Neural Networks—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
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
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
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
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
Generalizing Large Language Model Usability Across Resource-Constrained—0
Generalizing Machine Learning Evaluation through the Integration of Shannon Entropy and Rough Set Theory—0
General Uncertainty Estimation with Delta Variances—0
Generative emulation of chaotic dynamics with coherent prior—0
Generative Latent Neural PDE Solver using Flow Matching—0
Generative Modelling with Tensor Train approximations of Hamilton--Jacobi--Bellman equations—0
Generative Parameter Sampler For Scalable Uncertainty Quantification—0
Generative structured normalizing flow Gaussian processes applied to spectroscopic data—0
Generative vs. Discriminative modeling under the lens of uncertainty quantification—0
GeoFUSE: A High-Efficiency Surrogate Model for Seawater Intrusion Prediction and Uncertainty Reduction—0
Geophysical inverse problems with measurement-guided diffusion models—0
Give me (un)certainty -- An exploration of parameters that affect segmentation uncertainty—0
Global Framework for Emulation of Nuclear Calculations—0
Goal-oriented Uncertainty Quantification for Inverse Problems via Variational Encoder-Decoder Networks—0
Gradient-based Uncertainty Attribution for Explainable Bayesian Deep Learning—0
Gradient-enhanced deep neural network approximations—0
Grad-Shafranov equilibria via data-free physics informed neural networks—0
Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks—0
Graph Convolutional Neural Networks as Surrogate Models for Climate Simulation—0
Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects—0
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