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Shelby Cox

8 papers hereh-index 316 citations12 works total

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

author position
  • sole author1
  • first author3
  • middle author3
  • last author1

Across the 8 of 8 papers where every author was matched, so the position is known.

fields
  • math.CO3
  • math.AG2
  • math.HO1
  • math.ST1
  • q-bio.PE1
same name
  • Shelby Cox — 2 papers, h 1

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
20212026
most citedMaximum Likelihood Degrees of Brownian Motion Tree Models: Star Trees and Root Invariance

1 citations · 1 across the 8 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

math.AG2024

Tropicalizing binary geometries

Shelby Cox, Igor Makhlin

The type A cluster configuration space, commonly known as M0,n​, is the very affine part of the binary geometry associated with the associahedron. The tropicalization…

q-bio.PE2024

Group-Based Phylogenetic Models on 3-Sunlet Networks

Shelby Cox, Elizabeth Gross, Samuel Martin

Phylogenetic networks describe the evolution of a set of taxa for which reticulate events have occurred at some point in their evolutionary history. Of particular interest is when…

math.ST2024★ 1 cited

Maximum Likelihood Degrees of Brownian Motion Tree Models: Star Trees and Root Invariance

Jane Ivy Coons, Shelby Cox, Aida Maraj +1

A Brownian motion tree (BMT) model is a Gaussian model whose associated set of covariance matrices is linearly constrained according to common ancestry in a phylogenetic tree. We s…

math.AG2024

Homaloidal Polynomials and Gaussian Models of Maximum Likelihood Degree One

Shelby Cox, Pratik Misra, Pardis Semnani

We study the Gaussian statistical models whose log-likelihood function has a unique complex critical point, i.e., has maximum likelihood degree one. We exploit the connection devel…

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