1 citations · 2 across the 6 of their papers we have counts for
6 papers
Tensor network square root Kalman filter for online Gaussian process regression
Clara Menzen, Manon Kok, Kim Batselier
The state-of-the-art tensor network Kalman filter lifts the curse of dimensionality for high-dimensional recursive estimation problems. However, the required rounding operation can…
Online One-Dimensional Magnetic Field SLAM with Loop-Closure Detection
Manon Kok, Arno Solin
We present a lightweight magnetic field simultaneous localisation and mapping (SLAM) approach for drift correction in odometry paths, where the interest is purely in the odometry a…
Projecting basis functions with tensor networks for Gaussian process regression
Clara Menzen, Eva Memmel, Kim Batselier +1
This paper presents a method for approximate Gaussian process (GP) regression with tensor networks (TNs). A parametric approximation of a GP uses a linear combination of basis func…
Distributed multi-agent magnetic field norm SLAM with Gaussian processes
Frida Viset, Rudy Helmons, Manon Kok
Accurately estimating the positions of multi-agent systems in indoor environments is challenging due to the lack of Global Navigation Satelite System (GNSS) signals. Noisy measurem…
Mapping the magnetic field using a magnetometer array with noisy input Gaussian process regression
Thomas Edridge, Manon Kok
Ferromagnetic materials in indoor environments give rise to disturbances in the ambient magnetic field. Maps of these magnetic disturbances can be used for indoor localisation. A G…
Large-scale magnetic field maps using structured kernel interpolation for Gaussian process regression
Clara Menzen, Marnix Fetter, Manon Kok
We present a mapping algorithm to compute large-scale magnetic field maps in indoor environments with approximate Gaussian process (GP) regression. Mapping the spatial variations i…