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Aaron Smith

30 papers hereh-index 11351 citations45 works total

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

author position
  • sole author6
  • middle author6
  • last author18

Across the 30 of 30 papers where every author was matched, so the position is known.

fields
  • math.PR20
  • math.ST4
  • stat.CO3
  • cs.DS1
  • math.DS1
  • stat.ME1
same name
  • Aaron Smith — 37 papers, h 7
  • Aaron Smith — 28 papers, h 15
  • Aaron Smith — 18 papers, h 9
  • Aaron Smith — 10 papers, h 1
  • Aaron Smith — 8 papers, h 3
  • Aaron Smith — 6 papers, 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
20112026
most citedA Gibbs sampler on the n-simplex

14 citations · 37 across the 19 of their papers we have counts for

collaborators
Showing 2018 · math.PRShow all

4 papers · 2 filters

math.PR2018★ 1 cited

Mixing Times and Hitting Times for General Markov Processes

Robert M. Anderson, Haosui Duanmu, Aaron Smith

The hitting and mixing times are two fundamental quantities associated with Markov chains. In Peres and Sousi[PS2015] and Oliveira[Oli2012], the authors show that the mixing times…

math.PR2018★ 4 cited

Simple Conditions for Metastability of Continuous Markov Chains

Oren Mangoubi, Natesh S. Pillai, Aaron Smith

A family {Qβ​}β≥0​ of Markov chains is said to exhibit metastable mixing with modes Sβ(1)​,…,Sβ(k)​ if its spectral gap (or some other…

math.PR2018

Mixing of the Square Plaquette Model on a Critical Length Scale

Paul Chleboun, Aaron Smith

Plaquette models are short range ferromagnetic spin models that play a key role in the dynamic facilitation approach to the liquid glass transition. In this paper we study the dyna…

math.PR2018

Fast Mixing of Metropolis-Hastings with Unimodal Targets

James E. Johndrow, Aaron Smith

A well-known folklore result in the MCMC community is that the Metropolis-Hastings algorithm mixes quickly for any unimodal target, as long as the tails are not too heavy. Although…

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