2 papers
cs.LG2026
Robust Causal Discovery in Real-World Time Series with Power-Laws
Matteo Tusoni, Giuseppe Masi, Andrea Coletta +3
Exploring causal relationships in stochastic time series is a challenging yet crucial task with a vast range of applications, including finance, economics, neuroscience, and climat…
cs.LG2026
High-Quality Synthetic Financial Time-Series using a GAN-Diffusion Framework
Giuseppe Masi, Andrea Coletta, Novella Bartolini
In recent years, financial institutions and firms have increasingly adopted synthetic data to address data scarcity and to generate counterfactual market scenarios. However, reprod…