Latest Articles for Uncertainty Quantification

New method enhances confidence in model predictions against altered data.

A new approach improves coronary artery labeling accuracy in medical imaging.

A new approach enhances the safety of complex AI systems.

A new method enhances the effectiveness of LLMs for Open Information Extraction tasks.

A look into the importance of network analysis across various fields.

New method speeds up uncertainty analysis while maintaining tensor grid benefits.

A new method to enhance predictions in Bayesian deep learning by focusing on key parameters.

New techniques improve power flow learning for efficient electricity delivery.

Research reveals vulnerabilities in machine learning models through targeted uncertainty manipulation.

A look into the challenges and techniques of predicting infrequent events.

A method for efficient group sparse regression in data science.

A new method combines data-driven techniques with physical principles for better modeling.

Explore methods to enhance uncertainty quantification in event prediction models.

A software tool aids researchers in studying extreme weather events and their impact.

Research highlights the use of MPNNs to classify materials and predict properties.

Combining data sources enhances climate forecasting accuracy.

Improving Bayesian inference methods for ultrametric matrices in complex data analysis.

A new method boosts PDE solving speed while measuring prediction reliability.

Introducing a method for reliable uncertainty quantification in statistical learning.

A study on reliability and uncertainty in large language models.

A new kNN method improves mean and variance estimation with uncertainty assessment.

New methods enhance reliability of AI predictions, particularly in critical fields.

A new method enhances the accuracy of AI in diagnosing medical conditions.

This study uses machine learning to improve understanding of neutron star equations of state.

New methods improve understanding of oil spill movement through ocean models.

Introducing a method to assess reliability in language model outputs.

Assessing uncertainty in neural networks for improved scientific predictions.

A new method improves uncertainty estimation in atomistic simulations with deep learning.

A framework for certifying deep learning applications in safety-critical fields.

New methods improve object pose accuracy and uncertainty assessment in robotics.

A look at methods to improve model predictions and reduce uncertainty.

GUDR enhances UDR for better accuracy in uncertainty quantification.

New techniques improve uncertainty quantification for complex engineering models.

A new method improves anomaly detection by managing uncertainty effectively.

A method for generating synthetic data using Bayesian networks to protect privacy while allowing analysis.

An integrated approach to study phase transitions with uncertainties and injection boundaries.

New method enhances uncertainty quantification in DeepONets using Ensemble Kalman Inversion.

This article presents a method for improving uncertainty estimates in TinyML applications.

New methods enhance AI's ability to detect unexpected medical images.

New methods enhance safety by measuring confidence in self-driving vehicle decisions.