Daniel Amadori

Daniel Amadori

Post-graduate Research Grantee in Computer Science

DRIFTS: Distributed Robustness for Time Series is Feasible, Distributed, and Fun

Published in IEEE Conference on Artificial Intelligence (IEEE CAI26), 2026

Recommended citation: Amadori, D., Chini, E., Sala, P. (2026). "DRIFTS: Distributed Robustness for Time Series is Feasible, Distributed, and Fun." IEEE Conference on Artificial Intelligence (IEEE CAI26). https://ieeexplore.ieee.org/document/11536523

Read the paper here

DOI: 10.1109/CAI68641.2026.11536523

Recommended citation: Amadori, D., Chini, E., Sala, P. (2026). “DRIFTS: Distributed Robustness for Time Series is Feasible, Distributed, and Fun.” IEEE Conference on Artificial Intelligence (IEEE CAI26).