Latest Articles for Uncertainty

Explore how uncertainty affects machine learning predictions and methods to measure it.

Experts develop models to predict disease spread amid uncertainties.

A look at control systems and the role of state estimation in technology management.

Credal learning theory offers new insights for adapting machine learning models to changing data.

A new framework helps analyze explanations from large language models effectively.

Learn how SMPC balances safety and performance in uncertain systems.

A new method improves flow analysis by addressing uncertainty in FTLE data.

This research evaluates AI model confidence and explanation quality in noisy environments.

Enhancing safety in machines through better perception contracts and learning-based approaches.

This study highlights the importance of uncertainty in assessing Vision-Language Models.

Examining data analysis pipelines and methods to manage uncertainty in political research.

Research focuses on improving explanations and handling uncertainty in AV decision-making.

A look into the reliability of machine learning and deep neural networks.

Improving shear bias calibration is key to studying dark energy and the universe's expansion.

A new method to evaluate the accuracy of LLM outputs using local intrinsic dimensions.

New methods enhance aircraft path predictions for safer air traffic control.

A new model improves predictions for heavy rainfall events.

Improving the calibration of uncertainty enhances decision-making in various fields.

This article examines the rare production of four top quarks in particle collisions.

This article examines how differences impact group opinion formation.

ProbSAINT predicts used car prices while assessing uncertainty in predictions.

A new method aims to improve safety in mobile robots by addressing uncertainties.

A novel approach to reward over-optimization in language models using uncertainty estimation.

Introducing a new model for better predicting vehicle movements in traffic.

APRICOT enhances trust in language models by measuring answer confidence accurately.

Learn how to measure uncertainties in robotic pose estimation for better performance.

A new method enhances molecular simulations by targeting areas of uncertainty.

A new method enhances image quality in Magnetic Particle Imaging.

Tyche offers flexible, diverse segmentation options for medical imaging challenges.

A new method helps robots ask for help and reduces errors.

A new method improves surrogate modeling accuracy using physical principles.

Research aims to improve machine interpretation of 3D environments for safety.

This study examines how Bayesian methods can enhance malware detection systems.

A new AI method improves scheduling in uncertain task environments.

Learn how engineers deal with uncertainty for safer designs.

A new method improves moment estimation with less computation and greater accuracy.

This article discusses how data-driven methods improve control systems through simplified models.

How different communication methods influence decision-making in uncertain situations.

A new approach to improve uncertainty quantification in multi-dimensional time series data.

A new method enhances the optimization of complex simulations by reducing uncertainty.