High-dimensional approximation spaces of artificial neural networks and applications to partial differential equations. - Pierfrancesco Beneventano; Patrick Cheridito; Arnulf Jentzen; Philippe von Wurstemberger (CoRR, 2020)

Deep neural network approximation theory for high-dimensional functions. - Pierfrancesco Beneventano; Patrick Cheridito; Robin Graeber; Arnulf Jentzen; Benno Kuckuck (CoRR, 2021)

On the Trajectories of SGD Without Replacement. - Pierfrancesco Beneventano (CoRR, 2023)

How Neural Networks Learn the Support is an Implicit Regularization Effect of SGD. - Pierfrancesco Beneventano; Andrea Pinto; Tomaso A. Poggio (CoRR, 2024)

Edge of Stochastic Stability: Revisiting the Edge of Stability for SGD. - Arseniy Andreyev; Pierfrancesco Beneventano (CoRR, 2024)

Gradient Descent Converges Linearly to Flatter Minima than Gradient Flow in Shallow Linear Networks. - Pierfrancesco Beneventano; Blake Woodworth (CoRR, 2025)