Stochastic Processes on Sparse Graphs: Hydrodynamic Limits and Markov Approximations

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United States Simons Institute for the Theory of Computing
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Published on ● Video Link: https://www.youtube.com/watch?v=gXWrdVreBaA


Duration: 51:05
552 views
22

Kavita Ramanan (Brown University)
https://simons.berkeley.edu/node/22613
Graph Limits, Nonparametric Models, and Estimation

We consider interacting particle systems on suitable convergent sequences of sparse (or heterogeneous graphs) and show that the limiting dynamics of the associated neighborhood empirical measure process
(the so-called hydrodynamic limit) can be autonomously characterized in terms of a non-Markovian process. We then describe Markovian approximations to the latter and provide examples where they are exact. This includes joint work with G. Cocomello and A. Ganguly.



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Tags:
Simons Institute
theoretical computer science
UC Berkeley
Computer Science
Theory of Computation
Theory of Computing
Graph Limits Nonparametric Models and Estimation
Kavita Ramanan