Latest Articles for Predictive Modeling

A new method enhances parameter estimation for linear regression amid non-standard error distributions.

MA-COPP offers new insights into predicting outcomes in complex multi-agent settings.

Examining variance profiles in ridge regression for better predictive modeling.

Examining resampling techniques for better regression estimates and predictions.

Discover how new models improve predictions in mergers and acquisitions.

Enhancing State Space Models through better training techniques for time series data.

Discover how interpolation enhances the reliability of machine learning in science.

New methods provide clearer insights into algorithmic decisions using counterfactual explanations.

BARN combines BART and neural networks for improved prediction accuracy.

Introducing sharpness-aware minimization to improve feature construction in genetic programming.

QComp improves data completion accuracy in drug discovery, aiding faster research.

A new machine learning model improves seismic wave predictions for better disaster response.

DyS combines strong performance and interpretability for effective survival analysis.

New model enhances predictions by blending physics knowledge with advanced learning techniques.

A new method for integrating temporal logic into AI systems.

A new method enhances graph predictions with reliable uncertainty estimates.

Techniques for refining data in machine learning for better efficiency and accuracy.

PLCP offers reliable prediction sets across diverse populations, enhancing decision-making.

A look at how UHAT models process data sequences effectively.

A digital twin simulates hydrogen combustor behavior to improve gas turbine stability.

Introducing a new method to enhance state space models in dynamic systems.

A new method to improve predictive models using uncertain data.

A new model for predicting links in dynamic graphs with clear explanations.

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

A new method combines deep learning with polynomial techniques for improved function approximations.

A new method for better economic predictions using latent factors and kernel techniques.

A new method enhances healthcare predictions using external data sources.

This paper discusses how WALS enhances predictions in count data analysis.

New methods improve Kalman filtering efficiency and uncertainty estimates in high-dimensional settings.

Introducing Chimera, a new model for multivariate time series data analysis.

Exploring the role of machine learning in predicting material behaviors and challenges faced.

Learn how resampling techniques improve the stability of statistical findings.

A method using SGVMD and LSTM to enhance sales prediction accuracy.

This article discusses methods for creating narrow prediction intervals in changing data conditions.

A new MCMC method improves efficiency in complex data analysis.

A look into how links form and evolve in social networks.

A look at PCR's role in analyzing high-dimensional datasets.

A new framework for creating reliable and accurate machine learning classifiers.

This study explores the impact of predictions on individual actions and outcomes.

A look at regularized algorithms and their impact on machine learning performance.