Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...

Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

This study provides an important advance in credibility-based learning research by demonstrating how feedback reliability can shape reward learning biases within a carefully controlled bandit task.

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

Add a description, image, and links to the sparse-bayesian-learning topic page so that developers can more easily learn about it.

Start a Ray head node Connect and start Ray worker nodes via SSH Activate virtual environments and configure PYTHONPATH on all nodes 📌 Before running the script, ensure passwordless SSH access from ...

1 Minutia.AI Pte. Ltd., Singapore, Singapore 2 Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milano, Italy A representation of the cause-effect mechanism is ...

Accurate disaster prediction combined with reliable uncertainty quantification is crucial for timely and effective decision-making in emergency management. However, traditional deep learning methods ...