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Uncertainty Quantification

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Showing 151–200 of 2366 papers

TitleStatusHype
A Taylor Series Approach to Correction of Input Errors in Gaussian Process Regression—0
Data-Driven Calibration of Prediction Sets in Large Vision-Language Models Based on Inductive Conformal Prediction—0
Evaluating Uncertainty in Deep Gaussian ProcessesCode0
SOFARI-R: High-Dimensional Manifold-Based Inference for Latent Responses—0
Data-Driven Surrogate Modeling Techniques to Predict the Effective Contact Area of Rough Surface Contact Problems—0
Statistical Guarantees in Synthetic Data through Conformal Adversarial Generation—0
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification—0
Conditional Diffusion-Based Retrieval of Atmospheric CO2 from Earth Observing Spectroscopy—0
Achieving Distributive Justice in Federated Learning via Uncertainty QuantificationCode0
From predictions to confidence intervals: an empirical study of conformal prediction methods for in-context learning—0
Bayesian Federated Learning for Continual Training—0
Conformalized-KANs: Uncertainty Quantification with Coverage Guarantees for Kolmogorov-Arnold Networks (KANs) in Scientific Machine Learning—0
Uncertainty quantification of neural network models of evolving processes via Langevin sampling—0
Position: Bayesian Statistics Facilitates Stakeholder Participation in Evaluation of Generative AI—0
Learning Enhanced Structural Representations with Block-Based Uncertainties for Ocean Floor MappingCode0
Generative emulation of chaotic dynamics with coherent prior—0
Safety Monitoring for Learning-Enabled Cyber-Physical Systems in Out-of-Distribution Scenarios—0
Adaptive modelling of anti-tau treatments for neurodegenerative disorders based on the Bayesian approach with physics-informed neural networks—0
Exploring the Potential for Large Language Models to Demonstrate Rational Probabilistic BeliefsCode0
Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias Results—0
Riemannian Patch Assignment Gradient Flows—0
Safe Physics-Informed Machine Learning for Dynamics and Control—0
Uncertainty Quantification in Graph Neural Networks with Shallow Ensembles—0
Multi-Agent Reinforcement Learning Simulation for Environmental Policy Synthesis—0
Leave-One-Out Stable Conformal PredictionCode0
Advances in Surrogate Modeling for Biological Agent-Based Simulations: Trends, Challenges, and Future Prospects—0
Efficient Medical Image Restoration via Reliability Guided Learning in Frequency Domain—0
Bayesian Analysis of Interpretable Aging across Thousands of Lithium-ion Battery Cycles—0
Conformal Calibration: Ensuring the Reliability of Black-Box AI in Wireless Systems—0
Adaptive Shrinkage Estimation For Personalized Deep Kernel Regression In Modeling Brain TrajectoriesCode0
Conditional Conformal Risk Adaptation—0
A Novel Deep Learning Approach for Emulating Computationally Expensive Postfire Debris Flows—0
Conformalized Generative Bayesian Imaging: An Uncertainty Quantification Framework for Computational Imaging—0
ICBM community cancer registry analysis: a focus on Non-Hodgkin Lymphoma cases in missileers—0
Trustworthy AI Must Account for Intersectionality—0
Conformal Robust Beamforming via Generative Channel Models—0
Assumption-free fidelity bounds for hardware noise characterization—0
Adapting GT2-FLS for Uncertainty Quantification: A Blueprint Calibration StrategyCode0
Uncertainty-Aware Hybrid Machine Learning in Virtual Sensors for Vehicle Sideslip Angle Estimation—0
The challenge of uncertainty quantification of large language models in medicine—0
Explaining Uncertainty in Multiple Sclerosis Lesion Segmentation Beyond Prediction Errors—0
Adaptive Elicitation of Latent Information Using Natural Language—0
Randomised Postiterations for Calibrated BayesCG—0
Structured Extraction of Process Structure Properties Relationships in Materials Science—0
Bayesian LSTM for indoor temperature modeling—0
Quantifying the uncertainty of model-based synthetic image quality metrics—0
Operator Learning: A Statistical Perspective—0
Probabilistic Machine Learning for Noisy Labels in Earth Observation—0
Computing High-dimensional Confidence Sets for Arbitrary Distributions—0
Improving Counterfactual Truthfulness for Molecular Property Prediction through Uncertainty Quantification—0
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