Cesare Alippi

A frozen graph backbone effectively preserves past structural knowledge in continual multi-agent reinforcement learning, dramatically reducing forgetting and boosting transfer across tasks with distinct graph structures.

Longer context windows in time series forecasting aren't just about capturing dependencies—they're essential for reducing uncertainty in the underlying generative processes.

Time series generation can be dramatically improved by explicitly conditioning on semantic understanding, as demonstrated by a novel vision-centric framework.