Search Results - "Karjalainen, Joona"
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Clique and cycle frequencies in a sparse random graph model with overlapping communities
Published in Stochastic models (01-11-2024)“…A statistical network model with overlapping communities can be generated as a superposition of mutually independent random graphs of varying size. The model…”
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2
Mixing time of the conditional backward sampling particle filter
Published 29-12-2023“…The conditional backward sampling particle filter (CBPF) is a powerful Markov chain Monte Carlo sampler for general state space hidden Markov model smoothing…”
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Normal and stable approximation to subgraph counts in superpositions of Bernoulli random graphs
Published 13-03-2022“…J. Appl. Probab. 61 (2024) 401-419 The clustering property of complex networks indicates the abundance of small dense subgraphs in otherwise sparse networks…”
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On the Forgetting of Particle Filters
Published 15-09-2023“…We study the forgetting properties of the particle filter when its state - the collection of particles - is regarded as a Markov chain. Under a strong mixing…”
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Moment-based parameter estimation in binomial random intersection graph models
Published 13-04-2017“…Binomial random intersection graphs can be used as parsimonious statistical models of large and sparse networks, with one parameter for the average degree and…”
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Assortativity and bidegree distributions on Bernoulli random graph superpositions
Published 26-02-2020“…A probabilistic generative network model with $n$ nodes and $m$ overlapping layers is obtained as a superposition of $m$ mutually independent Bernoulli random…”
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7
Clique and cycle frequencies in a sparse random graph model with overlapping communities
Published 28-11-2019“…A statistical network model with overlapping communities can be generated as a superposition of mutually independent random graphs of varying size. The model…”
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8
Parameter estimators of random intersection graphs with thinned communities
Published 04-02-2018“…This paper studies a statistical network model generated by a large number of randomly sized overlapping communities, where any pair of nodes sharing a…”
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