Preprints:
Stochastic Analysis (Theory, Applications and Numerics):

• Diffusive behavior of transport noise on S^2 - S. Ephrati, E. Jansson, A. Papini, submitted 2025 (arxiv.org/pdf/2508.02707);

• Approximation of Levy-driven stochastic heat equation on the sphere - A. Lang, A. Papini, V. Schwarz, submitted 2025 (arxiv.org/abs/2507.05005) (Code);

• Coagulation Dynamics Under Random Fields: Turbulence Effetcs on Rain – A.Papini, 2023 (arxiv.org/abs/2111.12584);

• Epidemic Models as Scaling Limits of Individual Dynamics – F.Flandoli, F.Grotto, A.Papini, C.Ricci, 2022 (arxiv.org/abs/2007.05855).

Machine Learning:

• Eva Optimizer: Escaping Low-Curvature Traps in Deep Learning - A. Di Cecco, C. Metta, A. Papini, L. A. Bianchi, M. Parto, F. Morandin et all, submitted 2025; 

• Achieving Predictive Precision: Leveraging LSTM and Pseudo Labeling for Volvo's Discovery Challenge at ECML-PKDD 2024 - C .Metta, M. Gregnanin, A. Papini, S.G. Galfrè, et all, submitted 2024 (arXiv:2409.13877);

Publications:

1. Stochastic Analysis (Theory, Applications and Numerics):

• Average dissipation for stochastic transport equations with Lévy noise – F.Flandoli, A.Papini, M. Rehmeier. Stochastic Transport in Upper Ocean Dynamics II. STUOD 2023. Mathematics of Planet Earth, vol 12. Springer, Cham. (doi.org/10.1007/978-3-031-70660-8_3) (Code);

• Effect of Transport Noise on Kelvin-Helmholtz instability - F.Flandoli, S.Morlacchi, A.Papini. Stochastic Transport in Upper Ocean Dynamics II. STUOD 2022. Mathematics of Planet Earth, vol 11. Springer, Cham. (https://doi.org/10.1007/978-3-031-40094-0_3 ) (Code);
  
  

2. Mathematical Physics:

• Turbulence Enhancement of coagulation: the Role of Eddy Diffusion in Velocity –  A.Papini, F.Flandoli, R.Huang. Physica D: Nonlinear Phenomena, Volume 448, 2023. (doi.org/10.1016/j.physd.2023.133726 ) (Code).
  
  

3. Mathematical Analysis:

• Smoluchowski Coagulation equation with velocity component – F.Flandoli, R.Huang, A.Papini. SIAM Journal of Mathematical Analysis, Volume 56, 2024. (doi.org/10.1137/22M1540594).
  
  

4. Machine Learning:

• Increasing biases can be more efficient than increasing weights - C.Metta, M.Fantozzi, A.Papini, M.Parton, F.Morandin, et all. Advances in Data Analysis and Classification, Springer, 2025. (doi.org/10.1007/s11634-025-00649-2);

• Exploration and generalization in deep learning with SwitchPath activations - A. Di Cecco, A. Papini, C. Metta, M.Parton, F.Morandin, et all. - International Conference on Discovery Science, 2025. (doi.org/10.1007/s10994-025-06840-y);

• SwitchPath: Enhancing Exploration in Neural Networks Learning Dynamics - A. Di Cecco, A. Papini, C. Metta, M.Parton, F.Morandin, et all. - International Conference on Discovery Science, 2025. (link.springer.com/chapter/10.1007/978-3-031-78977-9_18);

• Improving Performance in Neural Networks by Dendrites-Activated Connections - C.Metta, M.Fantozzi, A.Papini, M.Parton, F.Morandin, et all. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024. (ieeexplore.ieee.org/document/10483732).

PhD Thesis:

• Turbulence Enhancement of Coagulating Processes - A. Papini (dx.doi.org/10.25429/papini-andrea_phd2023-12-14).

Master Thesis:

• A Mathematical Framework for Stochastic Gradient Algorithms - A. Papini (etd-10032019-105944/unrestricted/TesiMagistrale_PapiniAndrea.pdf)