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Physics Informed Topology Learning in Networks of Linear Dynamical
  Systems

Physics Informed Topology Learning in Networks of Linear Dynamical Systems

27 September 2018
Saurav Talukdar
Deepjyoti Deka
Harish Doddi
D. Materassi
Michael Chertkov
M. Salapaka
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Physics Informed Topology Learning in Networks of Linear Dynamical Systems"

6 / 6 papers shown
Title
Causal Structure Recovery of Linear Dynamical Systems: An FFT based
  Approach
Causal Structure Recovery of Linear Dynamical Systems: An FFT based Approach
M. S. Veedu
J. Melbourne
M. Salapaka
CML
68
0
0
05 Sep 2023
Information Theoretically Optimal Sample Complexity of Learning
  Dynamical Directed Acyclic Graphs
Information Theoretically Optimal Sample Complexity of Learning Dynamical Directed Acyclic Graphs
M. S. Veedu
Deepjyoti Deka
M. Salapaka
51
0
0
31 Aug 2023
Learning Distribution Grid Topologies: A Tutorial
Learning Distribution Grid Topologies: A Tutorial
Deepjyoti Deka
V. Kekatos
G. Cavraro
44
50
0
22 Jun 2022
Learning the Structure of Large Networked Systems Obeying Conservation
  Laws
Learning the Structure of Large Networked Systems Obeying Conservation Laws
Anirudh Rayas
A. Rajasekhar
Gautam Dasarathy
54
5
0
14 Jun 2022
Efficient and passive learning of networked dynamical systems driven by
  non-white exogenous inputs
Efficient and passive learning of networked dynamical systems driven by non-white exogenous inputs
Harish Doddi
Deepjyoti Deka
Saurav Talukdar
M. Salapaka
116
6
0
02 Oct 2021
Tractable learning in under-excited power grids
Tractable learning in under-excited power grids
Deepjyoti Deka
Harish Doddi
Sidhant Misra
M. Salapaka
13
2
0
04 May 2020
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