Browsing GI-M2NICA - Congresos, conferencias, etc. by Issue Date
Now showing items 1-11 of 11
-
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 ... -
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 ... -
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 ... -
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 ... -
Numerical Simulation of a Nonlinear Problem Arising in Heat Transfer and Magnetostatics
(MDPI AG, 2020-08-19)[Abstract] We present a numerical model that comprises a nonlinear partial differential equation. We apply an adaptive stabilised mixed finite element method based on an a posteriori error indicator derived for this ... -
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 ... -
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, ... -
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 ... -
Feedback control of stochastic gene switches using PIDE models
(Elsevier, 2022)[Abstract]: Achieving control of gene regulatory circuits is one of the goals of synthetic biology, as a way to regulate cellular functions for useful purposes (in biomedical, environmental or industrial applications). The ...
