3 papers
math.PR2026
A cylindrical neural approximation theorem for conditional laws of McKean-Vlasov equations with common noise
Nacira Agram, Reda Hmioui, Jan Rems
We introduce conditional cylindrical neural networks for approximating functionals of conditional laws in McKean-Vlasov equations with common noise. Fourier moments of the initial…
math.OC2026
Deep Learning for Energy Market Contracts: Dynkin Game with Doubly RBSDEs
Nacira Agram, Ihsan Arharas, Giulia Pucci +1
We formulate a Contract for Difference (CfD) with early exit options as a two-player zero-sum Dynkin game, reflecting the strategic interaction between an electricity producer and…
eess.SY2025
A Deep Learning Approach to Renewable Capacity Installation under Jump Uncertainty
Nacira Agram, Fred Espen Benth, Giulia Pucci +1
We study a stochastic model for the installation of renewable energy capacity under demand uncertainty and jump driven dynamics. The system is governed by a multidimensional Ornste…