22 citations · 42 across the 7 of their papers we have counts for
9 papers
Stable and Transferable Hyper-Graph Neural Networks
Mikhail Hayhoe, Hans Riess, Victor M. Preciado +1
We introduce an architecture for processing signals supported on hypergraphs via graph neural networks (GNNs), which we call a Hyper-graph Expansion Neural Network (HENN), and prov…
AutoEKF: Scalable System Identification for COVID-19 Forecasting from Large-Scale GPS Data
Francisco Barreras, Mikhail Hayhoe, Hamed Hassani +1
We present an Extended Kalman Filter framework for system identification and control of a stochastic high-dimensional epidemic model. The scale and severity of the COVID-19 emergen…
Data-Driven Control of the COVID-19 Outbreak via Non-Pharmaceutical Interventions: A Geometric Programming Approach
Mikhail Hayhoe, Francisco Barreras, Victor M. Preciado
In this paper we propose a data-driven model for the spread of SARS-CoV-2 and use it to design optimal control strategies of human-mobility restrictions that both curb the epidemic…
A Dynamical Approach to Efficient Eigenvalue Estimation in General Multiagent Networks
Mikhail Hayhoe, Francisco Barreras, Victor M. Preciado
We propose a method to efficiently estimate the eigenvalues of any arbitrary (potentially weighted and/or directed) network of interacting dynamical agents from dynamical observati…
Sparse estimation of Laplacian eigenvalues in multiagent networks
Mikhail Hayhoe, Francisco Barreras, Victor M. Preciado
We propose a method to efficiently estimate the Laplacian eigenvalues of an arbitrary, unknown network of interacting dynamical agents. The inputs to our estimation algorithm are m…
New bounds on the spectral radius of graphs based on the moment problem
Francisco Barreras, Mikhail Hayhoe, Hamed Hassani +1
Let be an undirected graph with adjacency matrix and spectral radius . Let and be, respectively, the number walks of length , closed…
SPECTRE: Seedless Network Alignment via Spectral Centralities
Mikhail Hayhoe, Francisco Barreras, Hamed Hassani +1
Network alignment consists of finding a structure-preserving correspondence between the nodes of two correlated, but not necessarily identical, networks. This problem finds applica…
Curing Epidemics on Networks using a Polya Contagion Model
Mikhail Hayhoe, Fady Alajaji, Bahman Gharesifard
We study the curing of epidemics of a network contagion, which is modelled using a variation of the classical Polya urn process that takes into account spatial infection among neig…
A Polya Contagion Model for Networks
Mikhail Hayhoe, Fady Alajaji, Bahman Gharesifard
A network epidemics model based on the classical Polya urn scheme is investigated. Temporal contagion processes are generated on the network nodes using a modified Polya sampling s…