Måns Magnusson

Senior Lecturer/Associate Professor at Department of Statistics

Short presentation

I am currently an associate professor in Statistics at the Department of Statistics, Uppsala University. More information can be found on my home page at mansmagnusson.com.

Bias in Legal Data for Generative AI

Sargeant, Holli; Magnusson, Måns

Part of Generative AI and Law (GenLaw’24’), 2024
Validating and Extracting Information from National Identification Numbers in R: The Case of Finland and Sweden

Kantanen, Pyry; Bülow, Erik; Lahtinen, Aleksi; Magnusson, Måns et al.

Part of The R Journal, p. 4-14, 2024
- DOI for Validating and Extracting Information from National Identification Numbers in R: The Case of Finland and Sweden
The Swedish parliament corpus 1867–2022

Yrjänäinen, Väinö; Mohammadi Norén, Fredrik; Borges, Robert; Jarlbrink, Johan et al.

Part of Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), p. 16100-16112, 2024
- Download full text (pdf) of The Swedish parliament corpus 1867–2022
Unbiased estimator for the variance of the leave-one-out cross-validation estimator for a Bayesian normal model with fixed variance

Sivula, Tuomas; Magnusson, Måns; Vehtari, Aki

Part of Communications in Statistics - Theory and Methods, p. 5877-5899, 2023
- DOI for Unbiased estimator for the variance of the leave-one-out cross-validation estimator for a Bayesian normal model with fixed variance
The Cambridge Law Corpus: A Dataset for Legal AI Research

Östling, Andreas; Sargeant, Holli; Xie, Huiyuan; Bull, Ludwig et al.

Part of Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 2023

Bias in Legal Data for Generative AI

Sargeant, Holli; Magnusson, Måns

Part of Generative AI and Law (GenLaw’24’), 2024
The Swedish parliament corpus 1867–2022

Yrjänäinen, Väinö; Mohammadi Norén, Fredrik; Borges, Robert; Jarlbrink, Johan et al.

Part of Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), p. 16100-16112, 2024
- Download full text (pdf) of The Swedish parliament corpus 1867–2022
The Cambridge Law Corpus: A Dataset for Legal AI Research

Östling, Andreas; Sargeant, Holli; Xie, Huiyuan; Bull, Ludwig et al.

Part of Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 2023
Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models

Terenin, Alexander; Magnusson, Måns; Jonsson, Leif

Part of Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), p. 2925-2934, 2020
- DOI for Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models
Robust, Accurate Stochastic Optimization for Variational Inference

Dhaka, Akash Kumar; Catalina, Alejandro; Andersen, Michael R.; Magnusson, Måns et al.

Part of Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 2020