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Uncertainty Quantification

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Showing 351–375 of 2366 papers

TitleStatusHype
Aggregation of Models, Choices, Beliefs, and Preferences—0
α-OCC: Uncertainty-Aware Camera-based 3D Semantic Occupancy Prediction—0
A Critical Synthesis of Uncertainty Quantification and Foundation Models in Monocular Depth Estimation—0
Flow Matching Meets PDEs: A Unified Framework for Physics-Constrained Generation—0
Comparing the quality of neural network uncertainty estimates for classification problems—0
Compressed particle methods for expensive models with application in Astronomy and Remote Sensing—0
Condensed Stein Variational Gradient Descent for Uncertainty Quantification of Neural Networks—0
A Soft Sensor Method with Uncertainty-Awareness and Self-Explanation Based on Large Language Models Enhanced by Domain Knowledge Retrieval—0
A Critical Analysis of Internal Reliability for Uncertainty Quantification of Dense Image Matching in Multi-view Stereo—0
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness—0
A generative foundation model for an all-in-one seismic processing framework—0
Model-Free Kernel Conformal Depth Measures Algorithm for Uncertainty Quantification in Regression Models in Separable Hilbert Spaces—0
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems—0
A robustness measure for singular point and index estimation in discretized orientation and vector fields—0
A generalized Bayes framework for probabilistic clustering—0
A Risk-Aware Adaptive Robust MPC with Learned Uncertainty Quantification—0
A Rigorous Uncertainty-Aware Quantification Framework Is Essential for Reproducible and Replicable Machine Learning Workflows—0
A General Framework for Uncertainty Quantification via Neural SDE-RNN—0
A Consistency-Based Loss for Deep Odometry Through Uncertainty Propagation—0
Combining Statistical Depth and Fermat Distance for Uncertainty Quantification—0
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods—0
A Bulirsch-Stoer algorithm using Gaussian processes—0
Combining additivity and active subspaces for high-dimensional Gaussian process modeling—0
A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers—0
Are vision language models robust to uncertain inputs?—0
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