3 papers
cs.LG2026
Causal Discovery on Irregular Time Series
Martim Penim, Ricardo Ribeiro Pereira, Jacopo Bono +3
Causal discovery methods have shown strong performance in temporal systems, but they typically rely on regular and discrete lag structures, limiting their applicability to regularl…
cs.LG2026
TEDD: Robust Detection of Unstable Temporal Features
Ricardo Ribeiro Pereira, Bruno Casal Laraña, Nádia Soares +1
When working with real-world temporal data, it is common to encounter features whose distribution is changing over time. The naive employment of Machine Learning models on this uns…
cs.LG2023
The GANfather: Controllable generation of malicious activity to improve defence systems
Ricardo Ribeiro Pereira, Jacopo Bono, João Tiago Ascensão +3
Machine learning methods to aid defence systems in detecting malicious activity typically rely on labelled data. In some domains, such labelled data is unavailable or incomplete. I…