Måns Magnusson
Måns Magnusson
Department of Statistics, Uppsala University, Sweden
Verified email at - Homepage
Cited by
Cited by
loo: Efficient leave-one-out cross-validation and WAIC for Bayesian models
A Vehtari, J Gabry, M Magnusson, Y Yao, PC Bürkner, T Paananen, ...
R package version 2 (1), 12, 2020
Pulling out the stops: Rethinking stopword removal for topic models
A Schofield, M Magnusson, D Mimno
Proceedings of the 15th Conference of the European Chapter of the …, 2017
Understanding text pre-processing for latent Dirichlet allocation
A Schofield, M Magnusson, L Thompson, D Mimno
Proceedings of the 15th conference of the European chapter of the …, 2017
Uncertainty in Bayesian leave-one-out cross-validation based model comparison
T Sivula, M Magnusson, AA Matamoros, A Vehtari
arXiv preprint arXiv:2008.10296, 2020
Risk of pancreatic cancer among individuals with hepatitis C or hepatitis B virus infection: a nationwide study in Sweden
J Huang, M Magnusson, A Törner, W Ye, AS Duberg
British journal of cancer 109 (11), 2917-2923, 2013
Leave-one-out cross-validation for Bayesian model comparison in large data
M Magnusson, A Vehtari, J Jonasson, M Andersen
International conference on artificial intelligence and statistics, 341-351, 2020
Bayesian Leave-One-Out Cross-Validation for Large Data
M Magnusson, MR Andersen, J Jonasson, A Vehtari
36th International Conference on Machine Learning, 7505-7525, 2019
Robust, accurate stochastic optimization for variational inference
AK Dhaka, A Catalina, MR Andersen, M Magnusson, J Huggins, A Vehtari
Advances in Neural Information Processing Systems 33, 10961-10973, 2020
The incidence of acute gastrointestinal illness in Sweden
FI Hansdotter, M Magnusson, S KüHlMANN-BereNzON, A Hulth, ...
Scandinavian Journal of Public Health 43 (5), 540-547, 2015
Prevailing effectiveness of the 2009 influenza A (H1N1) pdm09 vaccine during the 2010/11 season in Sweden
K Widgren, M Magnusson, P Hagstam, M Widerström, Å Örtqvist, ...
Eurosurveillance 18 (15), 2013
DOLDA-a regularized supervised topic model for high-dimensional multi-class regression
M Magnusson, L Jonsson, M Villani
Computational Statistics, 2020
Interpretable Word Embeddings via Informative Priors
MH Bodell, M Arvidsson, M Magnusson
EMNLP, 2019
Sparse partially collapsed mcmc for parallel inference in topic models
M Magnusson, L Jonsson, M Villani, D Broman
Journal of Computational and Graphical Statistics 27 (2), 449-463, 2018
Polya urn latent Dirichlet allocation: a doubly sparse massively parallel sampler
A Terenin, M Magnusson, L Jonsson, D Draper
IEEE Transactions on Pattern Analysis and Machine Intelligence 41 (7), 1709-1719, 2018
When are Bayesian model probabilities overconfident?
O Oelrich, S Ding, M Magnusson, A Vehtari, M Villani
arXiv preprint arXiv:2003.04026, 2020
Automatic localization of bugs to faulty components in large scale software systems using bayesian classification
L Jonsson, D Broman, M Magnusson, K Sandahl, M Villani, S Eldh
2016 IEEE International Conference on Software Quality, Reliability and …, 2016
Voices from the far right: a text analysis of Swedish parliamentary debates
M Magnusson, R Öhrvall, K Barrling, D Mimno
OSF, 2018
Finding the news lead in the data haystack: Automated local data journalism using crime data
M Magnusson, J Finnäs, L Wallentin
Computation+ Journalism Symposium, 2016
From documents to data: A framework for total corpus quality
M Hurtado Bodell, M Magnusson, S Mützel
Socius 8, 23780231221135523, 2022
PosteriorDB: A set of posteriors for Bayesian inference and probabilistic programming
M Magnusson, P Bürkner, A Vehtari
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