15 citations · 20 across the 7 of their papers we have counts for
7 papers
Asymptotically-informed neural networks for Black-Scholes implied volatility computation
Samira Amiriyan, Youness Boutaib
The computation of Black-Scholes implied volatility is a fundamental task in quantitative finance, underpinning option valuation, model calibration and risk management. Although im…
Separation capacity of linear reservoirs with random connectivity matrix
Youness Boutaib
A natural hypothesis for the success of reservoir computing in generic tasks is the ability of the untrained reservoir to map distinct input time series to separable reservoir stat…
The accessibility problem for geometric rough differential equations
Youness Boutaib
We show how to use geometric arguments to prove that the terminal solution to a rough differential equation driven by a geometric rough path can be obtained by driving the same equ…
Path classification by stochastic linear recurrent neural networks
Wiebke Bartolomaeus, Youness Boutaib, Sandra Nestler +1
We investigate the functioning of a classifying biological neural network from the perspective of statistical learning theory, modelled, in a simplified setting, as a continuous-ti…
A new definition of rough paths on manifolds
Youness Boutaib, Terry Lyons
Smooth manifolds are not the suitable context for trying to generalize the concept of rough paths on a manifold. Indeed, when one is working with smooth maps instead of Lipschitz m…
On Lipschitz maps and the Hölder regularity of flows
Youness Boutaib
This paper regroups some of the basic properties of Lipschitz maps and their flows. Many of the results presented here are classical in the case of smooth maps. We prove them here…
Dimension-free Euler estimates of rough differential equations
Youness Boutaib, Lajos Gergely Gyurkó, Terry Lyons +1
We give a dimension-free Euler estimation of solution of rough differential equations in term of the driving rough path. In the meanwhile, we prove that, the solution of rough diff…