A. Agazzi, G. Bruno, EMG, S. Saviozzi, M. Romito, Stochastic Scaling Limits and Synchronization by Noise in Deep Transformer Models, preprint.
P. Frosini, U. Fugacci, EMG, N. Quercioli, S. Scaramuccia, F. Tombari, The convex matching distance in multiparameter persistence, preprint.
EMG, A. Agazzi, D. Trevisan, Quantitative convergence of trained neural networks to Gaussian processes, NeurIPS 2025 (to appear).
P. Frosini, EMG, N. Quercioli, F. Tombari, Matching distance via the extended Pareto grid, SIAM Journal on Applied Algebra and Geometry (2025) .
Seminario de TDA, CUNEF, Mar 2026 - The Pareto grid in multiparametric persistence.
Jornadas de TDA 2026, University of Seville, Feb 2026 - The Convex matching distance in multiparametric persistence.
Mathematics for AI and ML, University of Rome Sapienza, Jan 2026 - Quantitative convergence of trained single layer deep neural networks to Gaussian processes.
CVG Seminar, Bern, Switzerland, Oct 2025 - Quantitative convergence of trained neural networks to Gaussian processes - Slides
Is AI Intelligence? A Dialogue Between Neuroscience and Physics, University of Roma Sapienza, Sep 2025 - Neural Manifold Learning through AI - A quick review of persistent homology - Slides and .ipynb
IMSV Retreat, Münchenwiler, Switzerland, Jan 2025 - Quantitative convergence of trained deep neural networks to Gaussian processes.
Gazteak RSME 2025, University of Bilbao, Jan 2025 - The extended Pareto grid in multiparameter persistent homology.
9th European Congress of Mathematics, Seville, Jul 2024 - Computation of the 2-parameter matching distance via the extended Pareto grid.
BYMAT, ICMAT, Madrid, Nov 2023 - A Morse Theory approach to the computation of the matching distance.