Randomized Signature Layers for Signal Extraction in Time Series Data. - Enea Monzio Compagnoni; Luca Biggio; Antonio Orvieto; Thomas Hofmann; Josef Teichmann (CoRR, 2022)

An SDE for Modeling SAM: Theory and Insights. - Enea Monzio Compagnoni; Luca Biggio; Antonio Orvieto; Frank Norbert Proske; Hans Kersting; Aurélien Lucchi (ICML, 2023)

On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics. - Enea Monzio Compagnoni; Anna Scampicchio; Luca Biggio; Antonio Orvieto; Thomas Hofmann; Josef Teichmann (IJCNN, 2023)

SDEs for Minimax Optimization. - Enea Monzio Compagnoni; Antonio Orvieto; Hans Kersting; Frank Proske; Aurélien Lucchi (AISTATS, 2024)

Unbiased and Sign Compression in Distributed Learning: Comparing Noise Resilience via SDEs. - Enea Monzio Compagnoni; Rustem Islamov; Frank Norbert Proske; Aurélien Lucchi (AISTATS, 2025)

Adaptive Methods through the Lens of SDEs: Theoretical Insights on the Role of Noise. - Enea Monzio Compagnoni; Tianlin Liu; Rustem Islamov; Frank Norbert Proske; Antonio Orvieto; Aurélien Lucchi (ICLR, 2025)

On the Interaction of Noise, Compression Role, and Adaptivity under (L0, L1)-Smoothness: An SDE-based Approach. - Enea Monzio Compagnoni; Rustem Islamov; Antonio Orvieto; Eduard Gorbunov (CoRR, 2025)