Nonsmooth automatic differentiation: a cheap gradient principle and other complexity results. - Jérôme Bolte; Ryan Boustany; Edouard Pauwels; Béatrice Pesquet-Popescu (CoRR, 2022)

On the complexity of nonsmooth automatic differentiation. - Jérôme Bolte; Ryan Boustany; Edouard Pauwels; Béatrice Pesquet-Popescu (ICLR, 2023)

A second-order-like optimizer with adaptive gradient scaling for deep learning. - Jérôme Bolte; Ryan Boustany; Edouard Pauwels; Andrei I. Purica (CoRR, 2024)

On the numerical reliability of nonsmooth autodiff: a MaxPool case study. - Ryan Boustany (Trans. Mach. Learn. Res., 2024)

When majority rules, minority loses: bias amplification of gradient descent. - François Bachoc; Jérôme Bolte; Ryan Boustany; Jean-Michel Loubes (CoRR, 2025)