7 citations · 13 across the 6 of their papers we have counts for
3 papers · 1 filter
A minimax optimal control approach for robust neural ODEs
Cristina Cipriani, Alessandro Scagliotti, Tobias Wöhrer
In this paper, we address the adversarial training of neural ODEs from a robust control perspective. This is an alternative to the classical training via empirical risk minimizatio…
From NeurODEs to AutoencODEs: a mean-field control framework for width-varying Neural Networks
Cristina Cipriani, Massimo Fornasier, Alessandro Scagliotti
The connection between Residual Neural Networks (ResNets) and continuous-time control systems (known as NeurODEs) has led to a mathematical analysis of neural networks which has pr…
A Measure Theoretical Approach to the Mean-field Maximum Principle for Training NeurODEs
Benoît Bonnet, Cristina Cipriani, Massimo Fornasier +1
In this paper we consider a measure-theoretical formulation of the training of NeurODEs in the form of a mean-field optimal control with -regularization of the control. We der…