Anton Rask Lundborg

Office 04.3.01

Department of Mathematical Sciences

University of Copenhagen

Universitetsparken 5

2100 København Ø

Denmark

I am a postdoc at the Copenhagen Causality Lab, University of Copenhagen. My current research focuses on non- and semiparametric inference for a variety of different data structures and problems.

My research interests include developing new methods with theoretical guarantees and analysing current methods in the fields of causal inference, semi- and nonparametric statistics and non-euclidean statistics.

I am also interested in more foundational and philosophical problems in statistics and causal inference in particular.

I am supervised by Niklas Pfister. Previously, I did a PhD under the supervision of Rajen Shah and Richard Samworth at the Statistical Laboratory, University of Cambridge and a master’s thesis under the supervision of Jonas Peters at the University of Copenhagen.

Keywords: statistics, theoretical statistics, conditional independence testing, causal inference, semiparametric statistics, nonparametric statistics, non-euclidean statistics

If you want to get in touch, email is your best bet! My email is arl@math.ku.dk.

Selected papers

arXiv

Perturbation-based Analysis of Compositional Data

Anton Rask Lundborg, and Niklas Pfister

2023

arXiv Bib

@misc{lundborg2023perturbationbased,
  doi = {10.48550/arXiv.2311.18501},
  author = {Lundborg, Anton Rask and Pfister, Niklas},
  title = {Perturbation-based Analysis of Compositional Data},
  year = {2023},
  eprint = {2311.18501},
  archiveprefix = {arXiv},
  primaryclass = {stat.ME}
}

arXiv

Model-based causal feature selection for general response types

Lucas Kook, Sorawit Saengkyongam, Anton Rask Lundborg, Torsten Hothorn, and Jonas Peters

2023

arXiv Bib

@misc{kook2023model,
  doi = {10.48550/ARXIV.2309.12833},
  author = {Kook, Lucas and Saengkyongam, Sorawit and Lundborg, Anton Rask and Hothorn, Torsten and Peters, Jonas},
  keywords = {Methodology (stat.ME), Statistics Theory (math.ST), Machine Learning (stat.ML)},
  title = {Model-based causal feature selection for general response types},
  publisher = {arXiv},
  year = {2023},
  copyright = {Creative Commons Attribution 4.0 International},
}

arXiv

The Projected Covariance Measure for assumption-lean variable significance testing

Anton Rask Lundborg, Ilmun Kim, Rajen D. Shah, and Richard J. Samworth

2022

arXiv Bib

@misc{lundborg2022projected,
  doi = {10.48550/ARXIV.2211.02039},
  author = {Lundborg, Anton Rask and Kim, Ilmun and Shah, Rajen D. and Samworth, Richard J.},
  keywords = {Statistics Theory (math.ST), Methodology (stat.ME), Machine Learning (stat.ML), FOS: Mathematics, FOS: Mathematics, FOS: Computer and information sciences, FOS: Computer and information sciences, 62G10},
  title = {The Projected Covariance Measure for assumption-lean variable significance testing},
  publisher = {arXiv},
  year = {2022},
  copyright = {Creative Commons Attribution 4.0 International},
}

News

Dec 2023	New paper on arXiv: Perturbation-based Analysis of Compositional Data
Sep 2023	New paper on arXiv: Model-based causal feature selection for general response types
Nov 2022	Paper on conditional independence testing for functional data is published in the Journal of The Royal Statistical Society: Series B.
Nov 2022	New paper on arXiv: The Projected Covariance Measure for assumption-lean variable significance testing
Oct 2022	Started postdoc at the University of Copenhagen supervised by Niklas Pfister.
Aug 2022	New paper on arXiv: Confounder Selection: Objectives and Approaches.
Jan 2021	First paper is on arXiv: Conditional Independence Testing in Hilbert Spaces with Applications to Functional Data.
Dec 2020	Gave a talk at CMStatistics 2020 about upcoming work on conditional independence testing for functional data.
Jan 2020	Started position as a PhD Student at the Unversity of Cambridge supervised by Rajen Shah and Richard Samworth.