Submitted and arXived work
Tuomas Sivola, Måns Magnusson, and Aki Vehtari. Unbiased estimator for the variance of the leave-one-out cross-validation estimator for a Bayesian normal model with fixed variance
arXiv
Tuomas Sivola, Måns Magnusson, and Aki Vehtari. Uncertainty in Bayesian Leave-One-Out Cross-Validation Based Model Comparison
arXiv
Oscar Oelrich, Shutong Ding, Aki Vehtari, Måns Magnusson, and Mattias Villani. When is Bayesian model probabilities overconfident?
arXiv
Måns Magnusson, Richard Öhrvall, Katarina Barrling, and David Mimno. Voices from the far right: a text analysis of Swedish parliamentary debates.
socarXiv
Published
Akash Kumar Dhaka, Alejandro Catalina, Michael Riis Andersen, Måns Magnusson, Jonathan H. Huggins, Aki Vehtari Robust, Accurate Stochastic Optimization for Variational Inference NeurIPS, 2020. arXiv proceedings
Alexander Terenin, Måns Magnusson, and Leif Jonsson. Sparse parallel training of hierarchical dirichlet process topic models. Emprical Methods in Natural Language Processing, 2020. arXiv proceedings
Måns Magnusson, Michael Riis Andersen, Johan Jonasson, and Aki Vehtari. Leave-one-out cross-validation for model comparison in large data. AISTATS, 2020.
arXiv
Miriam Hurtado Bodell, Martin Arvidsson, and Måns Magnusson. Interpretable word embeddings via informative priors. Emprical Methods in Natural Language Processing, 2019.
arXiv | proceedings
Måns Magnusson, Michael Riis Andersen, Johan Jonasson, and Aki Vehtari. Bayesian leave-one-out cross-validation for large data. International Conference on Machine Learning, 2019.
arXiv | proceedings
Måns Magnusson, Leif Jonsson, and Mattias Villani. DOLDA - a regularized supervised topic model for high-dimensional multi-class regression. Computational Statistics, 2019.
arXiv | journal
Alexander Terenin, Måns Magnusson, Leif Jonsson, and David Draper. Pólya urn latent dirichlet allocation: a sparse massively parallel sampler. Transactions on Pattern Analysis and Machine Intelligence, 2019.
arXiv | journal
Måns Magnusson, Leif Jonsson, Mattias Villani, and David Broman. Sparse partially collapsed MCMC for parallel inference in topic models. Journal of Computational and Graphical Statistics,27(2):449–463, 2018.
arXiv | journal
Alexandra Schofield, Måns Magnusson, and David Mimno. Pulling out the stops: Rethinking stop-word removal for topic models. EACL 2017, 2017.
proceedings
Leif Jonsson, David Broman, Måns Magnusson, Kristian Sandahl, Mattias Villani, and Sigrid Eldh. Automatic localization of bugs to faulty components in large scale software systems using bayesian classification. InSoftware Quality, Reliability and Security (QRS), 2016 IEEE International Conference on, pages 423–430. IEEE, 2016.
proceedings
Måns Magnusson, Jens Finnäs, and Leonard Wallentin. Finding the news lead in the data haystack:automated local data journalism using crime data. Computation+ Journalism Symposium, Palo Alto, CA, 2016.
proceedings
Frida Hansdotter, Måns Magnusson, Sharon Kühlmann-Berenzon, Anette Hulth, Kristian Sundström, Kjell-Olof Hedlund, and Yvonne Andersson. The incidence of acute gastrointestinal illness in Sweden. Scandinavian Journal of Social Medicine, 43(5):540–547, 2015.3
journal
Jiaqi Huang, Måns Magnusson, Anna Törner, Weimin Ye, and Ann-Sofi Duberg. Risk of pancreatic cancer among individuals with hepatitis C or hepatitis B virus infection: a nation wide study in Sweden. British journal of cancer, 109(11):2917–2923, 2013.
journal
Katarina Widgren, Måns Magnusson, P Hagstam, Micael Widerström, Åke Örtqvist, IM Einemo, P Follin, A Lindblom, S Mäkitalo, O Wik. Prevailing effectiveness of the 2009 influenza A (H1N1)pdm09 vaccine during the 2010/11 season in Sweden. Euro Surveillance, 18(15):20447, 2013.
journal
Johan Lindh, Måns Magnusson, Maria Grünewald, and Anette Hulth. Head lice surveillance on aderegulated OTC-sales market: A study using web query data. PloS one, 7(11):e48666, 2012.
journal