Latest Articles for Data Modeling

Sunbather aids scientists in understanding how exoplanet atmospheres evolve through mass-loss analysis.

Introducing GRAG to enhance language models' accuracy using graph structures.

Integrating SysCaps into energy modeling simplifies decision-making and improves predictions.

This article presents a novel approach to predicting time series data in finance.

Introducing a framework to better assess common factor models using generalized residuals.

A metapopulation model analyzes the impact of COVID-19 across North America.

GFlowNets enable effective sampling from complex distributions with strong generalization capabilities.

Diffusion models offer new ways to efficiently generate sea-ice data.

New frameworks for efficient modeling of complex networked systems in electrified vehicles.

Exploring how GNNs can model interactions in complex systems.

A look into the DLPM framework for data modeling and noise reduction.

A new approach improves dysfluency modeling for therapy and language learning.

A new framework that enhances graph generation flexibility and efficiency.

A new approach to estimate volcanic aerosol sources and their climate effects.

A look at how the Sun's magnetic fields affect space weather and technology on Earth.

New models improve analysis of count data with zeros and extreme values.

A new method to estimate household electricity consumption using predictive clustering trees.

A deep look at player strategies in cooperative and competitive games.

A new model helps scientists study Alzheimer's disease interactions.

A fresh approach improves long-term wave forecasting accuracy.

Researchers develop models to tackle evolving infectious diseases.

Samudra is a fast, advanced tool for ocean predictions vital for climate science.

A detailed model of the somatosensory cortex enhances understanding of brain responses.

Exploring methods for analyzing molecular interactions in chemistry.

A closer look at understanding asset connections in finance.

Learn how variational inference and normalizing flows improve statistical modeling.