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Nicholas J. Irons

3 papers here

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

author position
  • first author2
  • middle author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • stat.AP1
  • stat.ME1
  • stat.ML1
ORCID 0000-0002-9720-8259

identity via Semantic Scholar / OpenAlex

activity
20212024
most citedTriangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates

2 citations · 4 across the 3 of their papers we have counts for

collaborators

3 papers

stat.AP2024★ 2 cited

US COVID-19 school closure was not cost-effective, but other measures were

Nicholas J. Irons, Adrian E. Raftery

Non-pharmaceutical interventions (NPIs) in response to the COVID-19 pandemic necessitated a trade-off between the health impacts of viral spread and the social and economic costs o…

stat.ME2023

Easily Computed Marginal Likelihoods from Posterior Simulation Using the THAMES Estimator

Martin Metodiev, Marie Perrot-Dockès, Sarah Ouadah +2

We propose an easily computed estimator of marginal likelihoods from posterior simulation output, via reciprocal importance sampling, combining earlier proposals of DiCiccio et al…

stat.ML2021★ 2 cited

Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates

Nicholas J. Irons, Meyer Scetbon, Soumik Pal +1

Triangular flows, also known as Knöthe-Rosenblatt measure couplings, comprise an important building block of normalizing flow models for generative modeling and density estimation,…

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