GitHub

Gap-averaged flow simulations with Gaussian Process regression.

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 ...
Interesting Engineering

New adaptive system lets robots replicate human touch with far less training data

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 ...
eLife

Learning sequence-function relationships with scalable, interpretable Gaussian processes

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 ...
C&EN

Data-Driven Design of High-Temperature-Resistant Polyimides Using Hierarchical Gaussian Process Regression

School of Materials Science and Engineering, Beihang University, Beijing 100191, China State Key Laboratory of Artificial Intelligence for Materials Science, Beihang University, Beijing 100091, China ...
C&EN

Efficient Implementation of Gaussian Process Regression Accelerated Saddle Point Searches with Application to Molecular Reactions

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 ...
Phys.org

Gaussian processes provide a new path toward quantum machine learning

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 ...
IEEE

Adaptive Optimizable Gaussian Process Regression Linear Least Squares Regression Filtering Method for SEM Images

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 ...
Frontiers

Regression-based machine learning models for nitrate and chloride prediction in surface water in a small agricultural sand plain sub-watershed in southwestern Ontario, Canada

Machine learning (ML) models have proven to be an efficient technique for better understanding and quantification of surface water quality, especially in agricultural watersheds where considerable ...