Biography
Leonardo Bardi is an academic researcher at TU Chemnitz. His research focuses on Statistical learning, Generalized Bayesian learning, Weak dependence, Stochastic Partial Differential Equations and Ambit Stochastics.
Research Interests
- Statistical learning
- Generalized Bayesian learning
- Weak dependence
- Stochastic Partial Differential Equations
- Ambit Stochastics
Publications
Probabilistic forecast for raster datasets: a theory-guided machine learning methodology based on spatio-temporal Ornstein-Uhlenbeck processes
L. Bardi, I.V. Curato, L. Proietti
Forthcoming, 2026
Spatio-temporal probabilistic forecast using MMAF-guided learning
L. Bardi, I.V. Curato, L. Proietti
Arxiv preprint, 2026
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Participations
Conferences
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GSPD 2025 (Attendee)
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NordStat 2026 (Contributed Talk)
Workshops
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DYNSTOCH 2026 (Contributed Talk)
Summer Schools
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43rd Finnish Summer School on Probability and Statistics (Attendee)
-
ProbAI 2025 (Poster Presentation)
-
Lake Como School on Stochastic Dynamics: Foundations and Applications 2026 (Attendee)
-
2nd Summer School on PDEs and Randomness 2026 (Attendee)
Teaching
- Statistics in Data Science