Latest Articles for Uncertainty Quantification

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.

Researchers aim to improve predictions of partial differential equations using Neural Operators.

Understanding uncertainty quantification methods enhances engineering decision-making.

A method using AI enhances sound representation in various environments.

A method to estimate probability distributions in uncertain systems.

Explore how information theory enhances our knowledge of materials behavior.

Combining tensor completion with uncertainty quantification for better data insights.

New methods improve streamflow predictions for efficient water resource management.

Introducing a framework to quantify uncertainty in predictive models, especially in complex data spaces.

A new method enhances solution quality in medical imaging challenges.

A new method improves confidence scoring in language models using stable explanations.

New method enhances uncertainty quantification in adversarially trained models.

A fresh approach combines short-term and long-term ecological models for better predictions.

A new method helps robots understand user commands better.

A method combining SGD and privacy techniques for effective data analysis.

A framework to enhance Gaussian Process Regression's predictions and uncertainty measures.

A look at ensuring AI technologies are reliable and trustworthy.

A closer look at how Transformers learn from examples in varying contexts.

A look at how to handle errors in score-based generative models.

A new method improves prediction reliability using multiple data views.

This article discusses the importance of measuring uncertainty in AI predictions.

BayTTA merges TTA and BMA for better accuracy in medical imaging.

A look at methods to improve slurry flow management in various industries.

TrustAffinity enhances drug binding predictions and assesses uncertainty effectively.

This article discusses effective methods for improving uncertainty quantification in complex models using neural networks.

HydraGNN uses machine learning to accelerate materials discovery and modeling.

This study focuses on improving uncertainty measures in table detection tasks.

Study reveals how sound influences the dynamics of a conical flame.

A new method improves predictions in complex systems using deep learning and Gaussian processes.

Bayesian neural networks enhance material behavior predictions with uncertainty estimates.

A new method for tuning hyperparameters using Bayesian ideas.

A novel approach to assess treatment outcome uncertainty improves clinical decision-making.

An overview of the complexities in modeling neutron star merger events.

Discover how Huge Ensembles improve accuracy in weather predictions.

A data-driven method enhances confidence estimates in high-dimensional regression scenarios.