145 citations · 318 across the 12 of their papers we have counts for
12 papers
Modeling metallic fatigue data using the Birnbaum--Saunders distribution
Zaid Sawlan, Marco Scavino, Raul Tempone
This work employs the Birnbaum--Saunders distribution to model the fatigue life of metallic materials under cyclic loading and compares it with the normal distribution. Fatigue-lim…
Data-driven uncertainty quantification for constrained stochastic differential equations and application to solar photovoltaic power forecast data
Khaoula Ben Chaabane, Ahmed Kebaier, Marco Scavino +1
In this work, we extend the data-driven Itô stochastic differential equation (SDE) framework for the pathwise assessment of short-term forecast errors to account for the time-depen…
Computing f-Divergences and Distances of High-Dimensional Probability Density Functions -- Low-Rank Tensor Approximations
Alexander Litvinenko, Youssef Marzouk, Hermann G. Matthies +2
Very often, in the course of uncertainty quantification tasks or data analysis, one has to deal with high-dimensional random variables (RVs). A high-dimensional RV can be described…
Multilevel Density Functional Theory
Gioia Marrazzini, Tommaso Giovannini, Marco Scavino +3
We introduce a novel density-based multilevel approach in density functional theory. In this multilevel density functional theory (MLDFT), the system is partitioned in an active an…
Quantifying Uncertainty with a Derivative Tracking SDE Model and Application to Wind Power Forecast Data
Renzo Caballero, Ahmed Kebaier, Marco Scavino +1
We develop a data-driven methodology based on parametric Itô's Stochastic Differential Equations (SDEs) to capture the real asymmetric dynamics of forecast errors. Our SDE framewor…
eT 1.0: an open source electronic structure program with emphasis on coupled cluster and multilevel methods
Sarai D. Folkestad, Eirik F. Kjønstad, Rolf H. Myhre +14
The eT program is an open source electronic structure package with emphasis on coupled cluster and multilevel methods. It includes efficient spin adapted implementations of ground…
Spatial Poisson processes for fatigue crack initiation
Ivo Babuska, Zaid Sawlan, Marco Scavino +2
In this work we propose a stochastic model for estimating the occurrence of crack initiations on the surface of metallic specimens in fatigue problems that can be applied to a gene…
Ensemble-marginalized Kalman filter for linear time-dependent PDEs with noisy boundary conditions: Application to heat transfer in building walls
Marco Iglesias, Zaid Sawlan, Marco Scavino +2
In this work, we present the ensemble-marginalized Kalman filter (EnMKF), a sequential algorithm analogous to our previously proposed approach [1,2], for estimating the state and p…
Bayesian inferences of the thermal properties of a wall using temperature and heat flux measurements
Marco Iglesias, Zaid Sawlan, Marco Scavino +2
The assessment of the thermal properties of walls is essential for accurate building energy simulations that are needed to make effective energy-saving policies. These properties a…
Some probabilistic properties of fractional point processes
R. Garra, E. Orsingher, M. Scavino
This paper studies the first hitting times of generalized Poisson processes , related to Bernstein functions . For the space-fractional Poisson processes, , $t>0…
Bayesian inference and model comparison for metallic fatigue data
Ivo Babuska, Zaid Sawlan, Marco Scavino +2
In this work, we present a statistical treatment of stress-life (S-N) data drawn from a collection of records of fatigue experiments that were performed on 75S-T6 aluminum alloys.…
A hierarchical Bayesian setting for an inverse problem in linear parabolic PDEs with noisy boundary conditions
Fabrizio Ruggeri, Zaid Sawlan, Marco Scavino +1
In this work we develop a Bayesian setting to infer unknown parameters in initial-boundary value problems related to linear parabolic partial differential equations. We realistical…