Latest Articles for Predictive Modeling

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.

A new method improves data learning by maintaining prior information.

New methods enhance prediction accuracy and fairness in healthcare outcomes.

Leveraging language models improves predictions for tabular data across various fields.

A study comparing HAR model and machine learning in stock volatility forecasting.

Exploring the benefits of repeated data in training neural networks.

Exploring the role of transformers in predicting sequential data outcomes.

Stagewise boosting distributional regression improves analysis of complex data.

Using search data to predict car sales and flu rates.

A new approach to enhance model safety through prediction rejection.

New method improves reliability in measuring uncertainty in predictive models.

Data balancing is crucial for fairness and accuracy in machine learning models.

Learn about vortex-induced vibration and its impact on structures in fluid environments.

Explore how MPC manages uncertainty and model accuracy for effective control.

New algorithms improve online linear regression for dynamic environments.