GitHub

Gaussian Process State-Space Models

This repository provides a minimal, research-grade implementation of sparse variational Gaussian process state-space models (GPSSMs). The goal is convenience: generate time series, train a GPSSM, ...
GitHub

SVGP-KAN: Sparse Variational Gaussian Process Kolmogorov-Arnold Networks

SVGP-KAN is a library for building interpretable, probabilistic, and scalable neural networks. It merges the architecture of Kolmogorov-Arnold Networks (KANs) with the uncertainty quantification of ...
IEEE

Incremental Sparse Gaussian Process-Based Model Predictive Control for Trajectory Tracking of Unmanned Underwater Vehicles

Abstract: In this letter, a Model Predictive Control (MPC) approach based on the Incremental Sparse Gaussian Process (ISGP) is designed for trajectory tracking of Unmanned Underwater Vehicles (UUVs).
IEEE

Sequential training of semi-supervised classification based on sparse Gaussian process regression

Abstract: Gaussian process regression (GPR) is a very important Bayesian approach in machine learning applications. It has been extensively used in semi-supervised learning tasks. In this paper, we ...