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Quasi-Regression Monte-Carlo Method for Semi-Linear PDEs and BSDEs
(MDPI AG, 2019-08-06)
[Abstract] In this work we design a novel and efficient quasi-regression Monte Carlo algorithm in order to approximate the solution of discrete time backward stochastic differential equations (BSDEs), and we analyze the ...
First passage times as a measure of hysteresis in stochastic gene regulatory circuits
(Elsevier, 2022)
[Abstract]: In the context of phenotype switching and cell fate determination, numerousexperimental studies report hysteresis, despite the fact that the (forward) Chemical Master Equation governing the inherently stochastic ...
Deep Learning-Based Method for Computing Initial Margin †
(MDPI, 2021)
[Abstract] Following the guidelines of the Basel III agreement (2013), large financial institutions are forced to incorporate additional collateral, known as Initial Margin, in their transactions in OTC markets. Currently, ...
On the Adaptive Numerical Solution to the Darcy–Forchheimer Model †
(MDPI, 2021)
[Abstract] We considered a primal-mixed method for the Darcy–Forchheimer boundary value problem. This model arises in fluid mechanics through porous media at high velocities. We developed an a posteriori error analysis of ...
Quantum Arithmetic for Directly Embedded Arrays
(MDPI, 2021)
[Abstract] We describe a general-purpose framework to implement quantum algorithms relying upon an efficient handling of arrays. The cornerstone of the framework is the direct embedding of information into quantum amplitudes, ...
A hybrid numerical approach to quantify directivity patterns using phaseless hydroacoustic data
(European Acoustics Association, 2023)
[Abstract]: Hydroacoustic transducers have been used profusely in monitoring activities in coastal and oceanic marine environments for fishery purposes and the health evaluation of the seabed and its related biological ...
A New Technique for Improved Use of Thermal Energy from Waste Effluents
(MDPI AG, 2020-01-09)
[Abstract] Energy sustainability and environmental protection in general are at the heart of engineering and industry discussions. Countless efforts have been devoted to improving the energy efficiency of industrial processes ...
European and American Options Valuation by Unsupervised Learning with Artificial Neural Networks
(MDPI AG, 2020-08-19)
[Abstract]
Artificial neural networks (ANNs) have recently also been applied to solve partial differential equations (PDEs). In this work, the classical problem of pricing European and American financial options, based ...
Machine Learning to Compute Implied Volatility from European/American Options Considering Dividend Yield
(MDPI AG, 2020-09-15)
[Abstract]
Computing implied volatility from observed option prices is a frequent and challenging task in finance, even more in the presence of dividends. In this work, we employ a data-driven machine learning approach ...
Computation of Resonance Modes in Open Cavities with Perfectly Matched Layers
(MDPI AG, 2020-08-18)
[Abstract]
During the last decade, several authors have addressed that the Perfectly Matched Layers (PML) technique can be used not only for the computation of the near-field in time-dependent and time-harmonic scattering ...