Understanding Prior Probability in Bayesian Statistics

Learn how prior probability informs economic theory and decision-making in Bayesian statistics. Understand its role before collecting new data.
Frontiers

Coronary Artery Disease Prediction using Bayesian-Optimized Support Vector Machine with Feature Selection

The final, formatted version of the article will be published soon. Cardiovascular diseases, particularly Coronary Artery Disease (CAD), remain a leading cause of mortality worldwide. Invasive ...
IEEE

Analysis of Gas Pipeline Failure Factors Based on the Novel Bayesian Network by Machine Learning Optimization

Abstract: Assessing the failure of urban gas pipelines is crucial for identifying risk factors and preventing gas accidents that result in economic losses and casualties. Most previous studies on gas ...
Hosted on MSN

Calculating pi using only the Pythagoras theorem

Ready to unlock your full math potential? 🎓Subscribe for clear, fun, and easy-to-follow lessons that will boost your skills, build your confidence, and help you master math like a genius—one step at ...
IEEE

Bayesian Neural Networks via MCMC: A Python-Based Tutorial

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...
GitHub

Bayesian Continual Learning And Forgetting

MESU is a Bayesian framework that balances learning and forgetting by leveraging synaptic uncertainty, enabling continual learning without task boundaries while mitigating catastrophic forgetting, and ...