7 citations · 8 across the 6 of their papers we have counts for
6 papers · 1 filter
Risk-Averse Ensemble Control for Control-Affine Systems
Alessandro Scagliotti, Thomas M. Surowiec
A number of important modern applications in optimal control can be formulated as open loop control problems in which the underlying dynamical systems are subject to random inputs.…
Balanced quasistatic evolutions of critical points in metric spaces
Stefano Almi, Massimo Fornasier, Jona Klemenc +1
Quasistatic evolutions of critical points of time-dependent energies exhibit piecewise smooth behavior, making them useful for modeling continuum mechanics phenomena like elastic-p…
Trade-off Invariance Principle for minimizers of regularized functionals
Massimo Fornasier, Jona Klemenc, Alessandro Scagliotti
In this paper, we consider functionals of the form with , where varies in a set (without further structure). We first revi…
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…
Losing momentum in continuous-time stochastic optimisation
Kexin Jin, Jonas Latz, Chenguang Liu +1
The training of modern machine learning models often consists in solving high-dimensional non-convex optimisation problems that are subject to large-scale data. In this context, mo…