20 citations · 36 across the 9 of their papers we have counts for
3 papers · 1 filter
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…
On the Constrained Time-Series Generation Problem
Andrea Coletta, Sriram Gopalakrishan, Daniel Borrajo +1
Synthetic time series are often used in practical applications to augment the historical time series dataset for better performance of machine learning algorithms, amplify the occu…
K-SHAP: Policy Clustering Algorithm for Anonymous Multi-Agent State-Action Pairs
Andrea Coletta, Svitlana Vyetrenko, Tucker Balch
Learning agent behaviors from observational data has shown to improve our understanding of their decision-making processes, advancing our ability to explain their interactions with…