activity
20192025
most citedTowards Automated Satellite Conjunction Management with Bayesian Deep Learning

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

collaborators

5 papers

eess.SP2025

Characterization of Mega-Constellation Links for LEO Missions With Applications to EO and ISS Use Cases

G. Maiolini Capez, M. A. Caceres, C. P. Bridges +4

Satellite missions demand ever greater connectivity, especially in the LEO regime. In this paper, we introduce the new mega-constellation services in space paradigm: we show that m…

cs.LG2020★ 3 cited

Towards Automated Satellite Conjunction Management with Bayesian Deep Learning

Francesco Pinto, Giacomo Acciarini, Sascha Metz +7

After decades of space travel, low Earth orbit is a junkyard of discarded rocket bodies, dead satellites, and millions of pieces of debris from collisions and explosions. Objects i…

cs.LG2020★ 1 cited

Spacecraft Collision Risk Assessment with Probabilistic Programming

Giacomo Acciarini, Francesco Pinto, Sascha Metz +7

Over 34,000 objects bigger than 10 cm in length are known to orbit Earth. Among them, only a small percentage are active satellites, while the rest of the population is made of dea…

cs.DC2020

Diagonal Memory Optimisation for Machine Learning on Micro-controllers

Peter Blacker, Christopher Paul Bridges, Simon Hadfield

As machine learning spreads into more and more application areas, micro controllers and low power CPUs are increasingly being used to perform inference with machine learning models…

astro-ph.IM2019★ 1 cited

FDL: Mission Support Challenge

Luís F. Simões, Ben Day, Vinutha M. Shreenath +4

The Frontier Development Lab (FDL) is a National Aeronautics and Space Administration (NASA) machine learning program with the stated aim of conducting artificial intelligence rese…