| Fundamentals and recent developments in approximate Bayesian computation J Lintusaari, MU Gutmann, R Dutta, S Kaski, J Corander Systematic biology 66 (1), e66-e82, 2017 | 311 | 2017 |
| Elfi: Engine for likelihood-free inference J Lintusaari, H Vuollekoski, A Kangasrääsiö, K Skytén, M Järvenpää, ... Journal of Machine Learning Research 19 (16), 1-7, 2018 | 91 | 2018 |
| The role of local partial independence in learning of Bayesian networks J Pensar, H Nyman, J Lintusaari, J Corander International journal of approximate reasoning 69, 91-105, 2016 | 45 | 2016 |
| On the identifiability of transmission dynamic models for infectious diseases J Lintusaari, MU Gutmann, S Kaski, J Corander Genetics 202 (3), 911-918, 2016 | 36 | 2016 |
| Resolving outbreak dynamics using approximate Bayesian computation for stochastic birth–death models J Lintusaari, P Blomstedt, B Rose, T Sivula, MU Gutmann, S Kaski, ... Wellcome open research 4, 2019 | 11 | 2019 |
| ELFI: Engine for likelihood-free inference A Kangasrääsiö, J Lintusaari, K Skytén, M Järvenpää, H Vuollekoski, ... NIPS 2016 Workshop on Advances in Approximate Bayesian Inference, 2016 | 9 | 2016 |
| Meta-analysis of Bayesian analyses P Blomstedt, D Mesquita, J Lintusaari, T Sivula, J Corander, S Kaski arXiv preprint arXiv:1904.04484, 2019 | 5 | 2019 |
| PCSI-labeled directed acyclic graphs J Lintusaari Applied Mathematics 44, 1, 2014 | 2 | 2014 |
| Steps Forward in Approximate Computational Inference J Lintusaari Aalto University, 2019 | | 2019 |
| ELFI, a software package for likelihood-free inference J Lintusaari, H Vuollekoski, A Kangasrääsiö, K Skyten, M Järvenpää, ... International Conference on Machine Learning, 2017 | | 2017 |
Michael U. GutmannUniversity of EdinburghVerified email at ed.ac.uk
