Abstract: Gaussian process regression (GPR) models are becoming increasingly tightly integrated into robotic systems, particularly in the context of robot model predictive control (MPC) operating in ...

The published wheels are currently not built with LAMMPS. Thus, running multiscale simulations with molecular dynamics is not possible with this quick installation. For the full functionality it is ...

Researchers in Japan have developed an adaptive motion reproduction system that allows robots to generate human-like movements using surprisingly small amounts of training data. Despite rapid advances ...

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...

This important work introduces a family of interpretable Gaussian process models that allows us to learn and model sequence-function relationships in biomolecules. These models are applied to three ...

Gaussian Splatting is a cutting-edge 3D representation technique that models a scene as a set of learnable 3D Gaussian primitives. Each Gaussian defines a point in space with position, color, opacity, ...

ABSTRACT: The purpose of this study was to establish the mediating role of job satisfaction (JS) in the relationship between job involvement (JI) and psychological well-being (PWB). A cross-sectional ...

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...

Abstract: Scanning Electron Microscopy (SEM) images often suffer from noise contamination, which degrades image quality and affects further analysis. This research presents a complete approach to ...