Latest Articles for Predictive Modeling

A new method improves calibration in multi-class classification efficiently.

Learn how Bayesian methods improve predictions using past data.

A look at how GNNs analyze graphs and adapt to changes.

A novel method for fair data collection in predictive modeling.

New methods for sampling trajectories enhance predictions in various fields.

Probabilistic neural networks offer deeper insights into uncertainty in scientific modeling.

This study examines how ERM can function effectively with smooth data patterns.

This article discusses a new method for enhancing Extreme Learning Machines in various applications.

This paper investigates the impact of simplicity bias on one-dimensional dynamical systems.

A look at how gradient-enhanced models improve predictive accuracy.

This article presents a method to reduce bias in AI predictions.

Examining how early signals can predict crucial system changes.

PowerGraph enhances analysis of power grid failures through advanced learning techniques.

A method to separate relevant flow information for improved predictions and strategies.

Combining mechanistic and machine learning models for better glucose predictions.

DCC-Tree offers a new way to handle uncertainty in decision tree predictions.

Learn how decision trees aid in data-driven decisions and predictions.

Evaluating strategies for monitoring and managing structural deterioration for improved safety.

Convex Hull-aware Active Learning improves material stability assessments effectively.

Research on predicting vibrations in EVs using the Resoformer model.

Assessing machine learning models for reliable event forecasting.

Discover the latest developments in Quantum Monte Carlo techniques for chemistry.

Research investigates how network structure relates to stability using advanced methods.

A new method enhances the reliability of neural network predictions.

This article explores how deep learning improves predictions in healthcare survival analysis.

New methods improve accuracy and speed in predicting material fatigue.

Examining how LLMs can perform regression without additional training.

A new framework enhances prediction confidence through learning and reasoning.

Learn how selective predictions improve forecasting accuracy and decision-making in various fields.

A new approach enhances predictions in tabular data using LLMs.

Combining OOD detection and Conformal Prediction enhances model reliability.

This article discusses enhancing Additive Gaussian Processes using a new approach called Kernel Multigrid.

G-HANet combines tissue images and genomic data for improved cancer outcome predictions.

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.