7 citations · 7 across the 2 of their papers we have counts for
3 papers
stat.ML2026
A Decomposable Forward Process in Diffusion Models for Time-Series Forecasting
Francisco Caldas, Sahil Kumar, Cláudia Soares
We introduce a model-agnostic forward diffusion process for time-series forecasting that decomposes signals into spectral components, preserving structured temporal patterns such a…
astro-ph.EP2025
Analyzing Data Quality and Decay in Mega-Constellations: A Physics-Informed Machine Learning Approach
Katarina Dyreby, Francisco Caldas, Cláudia Soares
In the era of mega-constellations, the need for accurate and publicly available information has become fundamental for satellite operators to guarantee the safety of spacecrafts an…
cs.LG2024★ 7 cited
Precise and Efficient Orbit Prediction in LEO with Machine Learning using Exogenous Variables
Francisco Caldas, Cláudia Soares
The increasing volume of space objects in Earth's orbit presents a significant challenge for Space Situational Awareness (SSA). And in particular, accurate orbit prediction is cruc…