most citedDecentralised Semi-supervised Onboard Learning for Scene Classification in Low-Earth Orbit

8 citations · 10 across the 5 of their papers we have counts for

collaborators

5 papers

astro-ph.EP2023

Trajectory Optimisation of a Swarm Orbiting 67P/Churyumov-Gerasimenko Maximising Gravitational Signal

Rasmus Maråk, Emmanuel Blazquez, Pablo Gómez

Proper modelling of the gravitational fields of irregularly shaped asteroids and comets is an essential yet challenging part of any spacecraft visit and flyby to these bodies. Accu…

astro-ph.EP20232 cited

Investigation of the Robustness of Neural Density Fields

Jonas Schuhmacher, Fabio Gratl, Dario Izzo +1

Recent advances in modeling density distributions, so-called neural density fields, can accurately describe the density distribution of celestial bodies without, e.g., requiring a…

cs.LG20238 cited

Decentralised Semi-supervised Onboard Learning for Scene Classification in Low-Earth Orbit

Johan Östman, Pablo Gomez, Vinutha Magal Shreenath +1

Onboard machine learning on the latest satellite hardware offers the potential for significant savings in communication and operational costs. We showcase the training of a machine…

cs.DC2023

PAseos Simulates the Environment for Operating multiple Spacecraft

Pablo Gómez, Johan Östman, Vinutha Magal Shreenath +1

The next generation of spacecraft is anticipated to enable various new applications involving onboard processing, machine learning and decentralised operational scenarios. Even tho…

physics.comp-ph2022

NIDN: Neural Inverse Design of Nanostructures

Pablo Gómez, Håvard Hem Toftevaag, Torbjørn Bogen-Storø +2

In the recent decade, computational tools have become central in material design, allowing rapid development cycles at reduced costs. Machine learning tools are especially on the r…