Latest Articles for Gaussian Processes

A new approach improves control in uncertain environments using Gaussian processes.

Domino algorithm enhances electricity predictions, addressing data scarcity challenges.

New distributed methods enhance target tracking while reducing energy costs.

Discover the key benefits and applications of Gaussian Process methods in various fields.

Learn to analyze irregular time series data for better predictions and insights.

Advancements in reconstructing electric fields using Information Field Theory.

AUGUR simplifies finding optimal spots for molecular attachment using advanced techniques.

A new method improves Gaussian Process predictions by handling outliers effectively.

A new model improves analysis of longitudinal datasets with multiple covariates.

Exploring how Deep Gaussian Processes improve predictions by addressing complex data relationships.

Combining physics principles with data-driven methods for improved modeling.

A method to optimize decisions while ensuring safety in changing environments.

New modeling methods enhance understanding of neuronal activity and external factors.

A new approach to generating data using flow matching and Bayesian methods.

Research on modeling combustion behavior in hybrid rockets for improved safety.

Combining Gaussian processes and quantum computing offers faster energy management solutions.

New kernel improves Gaussian processes for accurate data predictions.

A study on how Gaussian processes analyze and forecast disease patterns.

Examining distant planets to uncover their mysteries and potential for life.

Exploring cosmic curvature helps reveal the universe's shape and expansion.

A look at domain adaptation, privacy, and federated learning in data science.

MOLPIPx aids scientists in accurately modeling molecular movements using advanced techniques.

A new model combines speed and efficiency for data analysis.

Learn how to simplify Gaussian processes for effective predictions without losing essence.

Integrating learning models into control systems leads to smarter robots and cars.

Boundary Ehrenpreis-Palamodov Gaussian Processes improves accuracy in solving PDEs.

New methods enhance causal analysis of spatial data using neural networks.

Discover how quantum computing shapes machine learning through innovative networks.

A fresh method enhances our grasp of particle physics.

Research combines seismic models to enhance predictions and reduce uncertainty in earthquake impacts.

FMGP improves DNN predictions by estimating uncertainty, crucial for high-stakes applications.

Learn how global optimization improves decision-making across various fields.

A new method simplifies RF mapping with fewer samples and real-time adaptability.

New methods in active learning boost model efficiency and tackle uncertainty.

Discover how DGPs sharpen images and handle uncertainty.

Learn how devices collaborate without sharing personal data.

New method fills data gaps using deep learning and satellite observations.

Discover advanced optimization methods transforming modern aircraft design.

Learn how to enhance image classifiers' reliability against distortions.

New methods improve how we locate items in large spaces.