| posteriordb: Testing, Benchmarking and Developing Bayesian Inference Algorithms M Magnusson, J Torgander, PC Bürkner, L Zhang, B Carpenter, A Vehtari arXiv preprint arXiv:2407.04967, 2024 | 12* | 2024 |
| Formalising Anti-Discrimination Law in Automated Decision Systems H Sargeant, M Magnusson arXiv preprint arXiv:2407.00400, 2024 | | 2024 |
| The Swedish Parliament Corpus 1867–2022 VA Yrjänäinen, FM Norén, R Borges, J Jarlbrink, LÅ Brorsson, AP Olsson, ... Proceedings of the 2024 Joint International Conference on Computational …, 2024 | | 2024 |
| Unbiased estimator for the variance of the leave-one-out cross-validation estimator for a Bayesian normal model with fixed variance T Sivula, M Magnusson, A Vehtari Communications in Statistics-Theory and Methods 52 (16), 5877-5899, 2023 | 9 | 2023 |
| The cambridge law corpus: a dataset for legal AI research A Östling, H Sargeant, H Xie, L Bull, A Terenin, L Jonsson, M Magnusson, ... Advances in Neural Information Processing Systems 2023, 2023 | 5* | 2023 |
| The transformation of ‘the political’in post-war Sweden F Norén, J Jarlbrink, A Borg, E Edoff, M Magnusson Newspapers–A New Eldorado for Historians?, 411, 2022 | 2 | 2022 |
| From documents to data: A framework for total corpus quality M Hurtado Bodell, M Magnusson, S Mützel Socius 8, 23780231221135523, 2022 | 11 | 2022 |
| Probabilistic Embeddings with Laplacian Graph Priors V Yrjänäinen, M Magnusson arXiv preprint arXiv:2204.01846, 2022 | | 2022 |
| Rapid mixing in unimodal landscapes and efficient simulatedannealing for multimodal distributions J Jonasson, M Magnusson arXiv preprint arXiv:2101.10004, 2021 | 1 | 2021 |
| Multilingual comparable corpora of parliamentary debates ParlaMint 1.0 T Erjavec, V Grigorova, N Ljubešić, M Ogrodniczuk, P Osenova, A Pančur, ... CLARIN ERIC, 2020 | 8 | 2020 |
| 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 | 91 | 2020 |
| 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 | 45 | 2020 |
| When are Bayesian model probabilities overconfident? O Oelrich, S Ding, M Magnusson, A Vehtari, M Villani arXiv preprint arXiv:2003.04026, 2020 | 22 | 2020 |
| 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 | 788* | 2020 |
| 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 | 33 | 2020 |
| DOLDA-a regularized supervised topic model for high-dimensional multi-class regression M Magnusson, L Jonsson, M Villani Computational Statistics, 2020 | 24* | 2020 |
| Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models A Terenin, M Magnusson, L Jonsson EMNLP, 2020 | 2 | 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 | 39 | 2019 |
| Interpretable Word Embeddings via Informative Priors MH Bodell, M Arvidsson, M Magnusson EMNLP, 2019 | 24 | 2019 |
| 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 | 21 | 2018 |
Aki VehtariProfessor, Aalto University在 aalto.fi 的电子邮件经过验证
