3 citations · 3 across the 7 of their papers we have counts for
3 papers · 1 filter
Communication-Efficient Learning for Satellite Constellations
Ruxandra-Stefania Tudose, Moritz H. W. Grüss, Grace Ra Kim +2
Satellite constellations in low-Earth orbit are now widespread, enabling positioning, Earth imaging, and communications. In this paper we address the solution of learning problems…
Bringing Federated Learning to Space
Grace Kim, Filip Svoboda, Nicholas Lane
As Low Earth Orbit (LEO) satellite constellations rapidly expand to hundreds and thousands of spacecraft, the need for distributed on-board machine learning becomes critical to add…
Space for Improvement: Navigating the Design Space for Federated Learning in Satellite Constellations
Grace Kim, Luca Powell, Filip Svoboda +1
Space has emerged as an exciting new application area for machine learning, with several missions equipping deep learning capabilities on-board spacecraft. Pre-processing satellite…