Abstract: This paper introduces an active learning framework for manifold Gaussian Process (GP) regression, combining manifold learning with strategic data selection to improve accuracy in ...

ABSTRACT: Despite the critical role teachers play in shaping educational outcomes, increasing workload and burnout remain pervasive challenges that threaten their wellbeing and job satisfaction, ...

Abstract: Aeromagnetic gradient tensor interpolation is a critical but challenging step in geophysical data processing, essential for transforming sparse, non-planar survey data into regular grids for ...

A serial build of LAMMPS is provided for most platforms which allows testing all of GaPFlow's functionality. For production simulations it is however recommended to ...

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 ...

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 ...

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 ...