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M. Marsili

121 papers hereh-index 447k citations242 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author4
  • first author13
  • middle author58
  • last author44

Across the 119 of 121 papers where every author was matched, so the position is known.

fields
  • cond-mat.stat-mech43
  • physics.soc-ph20
  • cond-mat.dis-nn10
  • physics.data-an6
  • q-fin.GN5
  • cond-mat4
same name
  • M. Marsili — 8 papers, h 18
  • M. Marsili — 5 papers, h 5
  • M. Marsili — 4 papers, h 6
  • M. Marsili — 1 paper, h 2
  • M. Marsili — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
19942023
most citedTheory of Rumour Spreading in Complex Social Networks

796 citations · 5.3k across the 118 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

stat.ME2018★ 19 cited

Minimum Description Length codes are critical

Ryan John Cubero, Matteo Marsili, Yasser Roudi

In the Minimum Description Length (MDL) principle, learning from the data is equivalent to an optimal coding problem. We show that the codes that achieve optimal compression in MDL…

physics.data-an2018★ 50 cited

Statistical Criticality arises in Most Informative Representations

Ryan John Cubero, Junghyo Jo, Matteo Marsili +2

We show that statistical criticality, i.e. the occurrence of power law frequency distributions, arises in samples that are maximally informative about the underlying generating pro…

q-bio.NC2018

Multiscale relevance and informative encoding in neuronal spike trains

Ryan John Cubero, Matteo Marsili, Yasser Roudi

Neuronal responses to complex stimuli and tasks can encompass a wide range of time scales. Understanding these responses requires measures that characterize how the information on…

cond-mat.stat-mech2018★ 9 cited

On Maximum Entropy and Inference

Luigi Gresele, Matteo Marsili

Maximum Entropy is a powerful concept that entails a sharp separation between relevant and irrelevant variables. It is typically invoked in inference, once an assumption is made on…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.