activity
20192026
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

cs.LG2026

LunarFM: A Shared Multimodal Representation of the Moon's Surface

Marc Girona-Mata, Jakob Gawlikowski, Sumit Goski +6

The renewed global focus on lunar exploration, driven by the prospect of in-situ resource utilization and a sustained human presence on the Moon, has created growing demand for acc…

cs.NE2026

Benchmarking the Energy Cost of Assurance in Neuromorphic Edge Robotics

Sylvester Kaczmarek

Deploying trustworthy artificial intelligence on edge robotics imposes a difficult trade-off between high-assurance robustness and energy sustainability. Traditional defense mechan…

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…

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…