Numerical modeling of ore-forming dynamics and 3D mineral prospectivity modeling are pivotal for deep mineral exploration, though each has inherent constraints. Commercial software such as FIDAP and ...

This repository contains my solutions to the lab sessions of the course Numerical Analysis for Machine Learning, taught by Professor Edie Miglio and Matteo Caldana during the Academic Year 2024–2025.

As the core equipment in industrial production, rotating machinery bearings play a critical role. However, traditional feature extraction algorithms for vibration signals are susceptible to noise ...

Abstract: In recent years, High Entropy Alloys (HEAs) have gained significant interest due to their unique properties such as high strength, wear resistance, and high temperature stability. However, ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

Beijing Advanced Innovation Center for Materials Genome Engineering, Department of Physical Chemistry, University of Science and Technology Beijing, Beijing 100083, China ...

Large Language Models (LLMs) generate step-by-step responses known as Chain-of-Thoughts (CoTs), where each token contributes to a coherent and logical narrative. To improve the quality of reasoning, ...

What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the basis or foundation in machine learning. In this video, we will learn what is ...

Machine learning (ML) is a subset of AI where a system learns patterns from data and makes decisions without being explicitly programmed for each outcome. In software development, this technology ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of payments. We live in a world where machines can understand speech, recognize faces, and even generate ...

Sample selection improves the efficiency and effectiveness of machine learning models by providing informative and representative samples. Typically, samples can be modeled as a sample graph, where ...