83 citations · 256 across the 14 of their papers we have counts for
14 papers
Inverse modeling of porous flow through deep neural networks: the case of coffee percolation
Antoniorenee Barletta, Salvatore Cuomo, Nadaniela Egidi +2
This work addresses the inverse problem of espresso coffee extraction, in which one aims to reconstruct the brewing conditions that generate a desired chemical profile in the final…
The effect of time discretization on the solution of parabolic PDEs with ANNs
Francesco Calabrò, Salvatore Cuomo, Daniela di Serafino +2
We investigate the resolution of parabolic PDEs via Extreme Learning Machine (ELMs) Neural Networks, which have a single hidden layer and can be trained at a modest computational c…
A sojourn-based approach to semi-Markov Reinforcement Learning
Giacomo Ascione, Salvatore Cuomo
In this paper we introduce a new approach to discrete-time semi-Markov decision processes based on the sojourn time process. Different characterizations of discrete-time semi-Marko…
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next
Salvatore Cuomo, Vincenzo Schiano di Cola, Fabio Giampaolo +3
Physics-Informed Neural Networks (PINN) are neural networks (NNs) that encode model equations, like Partial Differential Equations (PDE), as a component of the neural network itsel…
Heterogeneous Data Fusion Considering Spatial Correlations using Graph Convolutional Networks and its Application in Air Quality Prediction
Zhengjing Ma, Gang Mei, Salvatore Cuomo +1
Heterogeneous data are commonly adopted as the inputs for some models that predict the future trends of some observations. Existing predictive models typically ignore the inconsist…
Kernel-Based Models for Influence Maximization on Graphs based on Gaussian Process Variance Minimization
Salvatore Cuomo, Wolfgang Erb, Gabriele Santin
The inference of novel knowledge, the discovery of hidden patterns, and the uncovering of insights from large amounts of data from a multitude of sources make Data Science (DS) to…
Julia Language in Machine Learning: Algorithms, Applications, and Open Issues
Kaifeng Gao, Gang Mei, Francesco Piccialli +3
Machine learning is driving development across many fields in science and engineering. A simple and efficient programming language could accelerate applications of machine learning…
Adaptive RBF Interpolation for Estimating Missing Values in Geographical Data
Kaifeng Gao, Gang Mei, Salvatore Cuomo +2
The quality of datasets is a critical issue in big data mining. More interesting things could be mined from datasets with higher quality. The existence of missing values in geograp…
Degree Distribution of Delaunay Triangulations
Gang Mei, Nengxiong Xu, Salvatore Cuomo
Delaunay triangulation can be considered as a type of complex networks. For complex networks, the degree distribution is one of the most important inherent characteristics. In this…
Computational issues and numerical experiments for Linear Multistep Method Particle Filtering
Daniela Calvetti, Salvatore Cuomo, Monica Pragliola +2
The Linear Multistep Method Particle Filter (LMM PF) is a method for predicting the evolution in time of a evolutionary system governed by a system of differential equations. If so…
An error estimate of Gaussian Recursive Filter in 3Dvar problem
S. Cuomo, R. Farina, A. Galletti +1
Computational kernel of the three-dimensional variational data assimilation (3D-Var) problem is a linear system, generally solved by means of an iterative method. The most costly p…
A Revised Scheme to Compute Horizontal Covariances in an Oceanographic 3D-VAR Assimilation System
R. Farina, S. Dobricic, A. Storto +2
We propose an improvement of an oceanographic three dimensional variational assimilation scheme (3D-VAR), named OceanVar, by introducing a recursive filter (RF) with the third orde…
Surface Reconstruction from Scattered Point via RBF Interpolation on GPU
Salvatore Cuomo, Ardelio Gallettiy, Giulio Giuntay +1
In this paper we describe a parallel implicit method based on radial basis functions (RBF) for surface reconstruction. The applicability of RBF methods is hindered by its computati…
A PCG Implementation of an Elliptic Kernel in an Ocean Global Circulation Model Based on GPU Libraries
Salvatore Cuomo, Pasquale De Michele, Raffaele Farina +1
In this paper an inverse preconditioner for the numerical solution of an elliptic Laplace prob- lem of a global circulation ocean model is presented. The inverse preconditiong tech…