Search Results for author: Francesco Sorrentino

Found 11 papers, 2 papers with code

Optimizing time-shifts for reservoir computing using a rank-revealing QR algorithm

no code implementations29 Nov 2022 Joseph D. Hart, Francesco Sorrentino, Thomas L. Carroll

Reservoir computing is a recurrent neural network paradigm in which only the output layer is trained.

Symmetry-driven network reconstruction through pseudobalanced coloring optimization

no code implementations15 Nov 2021 Ian Leifer, David Phillips, Francesco Sorrentino, Hernán A. Makse

For that reason, a method to find pseudosymmetries and repair networks based on those symmetries is important when analyzing real world networks.

Link Prediction

Matryoshka and Disjoint Cluster Synchronization of Networks

no code implementations11 Nov 2021 Amirhossein Nazerian, Shirin Panahi, Ian Leifer, David Phillips, Hernan Makse, Francesco Sorrentino

For each pair of clusters, we distinguish between three different cases: Matryoshka Cluster Synchronization (when the range of the stability of the synchronous solution for one cluster is included in that of the other cluster), Partially Disjoint Cluster Synchronization (when the ranges of stability of the synchronous solutions partially overlap), and Complete Disjoint Cluster Synchronization (when the ranges of stability of the synchronous solutions do not overlap.)

Cluster Synchronization of Networks via a Canonical Transformation for Simultaneous Block Diagonalization of Matrices

1 code implementation28 Sep 2021 Shirin Panahi, Isaac Klickstein, Francesco Sorrentino

Our approach has several advantages as it allows us to: (1) decouple the stability problem into subproblems of minimal dimensionality while preserving physically meaningful information; (2) study stability of both orbital and equitable partitions of the network nodes and (3) obtain a parametrization of the problem in a small number of parameters.

Reservoir Computers with Random and Optimized Time-Shifts

no code implementations29 Aug 2021 Enrico Del Frate, Afroza Shirin, Francesco Sorrentino

We investigate the effects of application of random time-shifts to the readouts of a reservoir computer in terms of both accuracy (training error) and performance (testing error.)

Reservoir Computers Modal Decomposition and Optimization

no code implementations13 Jan 2021 Chad Nathe, Enrico Del Frate, Thomas Carroll, Louis Pecora, Afroza Shirin, Francesco Sorrentino

We then take a parametric approach in which the eigenvalues are parameters that can be appropriately designed and optimized.

Data-driven Optimized Control of the COVID-19 Epidemics

no code implementations4 Sep 2020 Afroza Shirin, Yen Ting Lin, Francesco Sorrentino

We then introduce a time-varying control input that represents the level of social distancing imposed on the population of a given area and solve an optimal control problem with the goal of minimizing the impact of social distancing on the economy in the presence of relevant constraints, such as a desired level of suppression for the epidemics at a terminal time.

Generating Graphs with Symmetry

1 code implementation15 Aug 2018 Isaac Klickstein, Francesco Sorrentino

In the field of complex networks and graph theory, new results are typically tested on graphs generated by a variety of algorithms such as the Erd\H{o}s-R\'{e}nyi model or the Barab\'{a}si-Albert model.


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