Workshop papers by Marko Järvenpää
Järvenpää, M., Vehtari, A., and Marttinen, P. (2019). Batch simulations and uncertainty quantification in Gaussian process surrogate-based approximate Bayesian computation. 2nd Symposium on Advances in Approximate Bayesian Inference. Online
Järvenpää, M., Sater, M.R.A., Lagoudas, K.G., Blainey, P.C., Miller, L.G., McKinnell, J.A., Huang, S.S., Grad, Y.H. and Marttinen P. (2019). A Bayesian model of acquisition and clearance of bacterial colonization incorporating within-host variation. The 2019 ICML Workshop on Computational Biology. Online
Järvenpää, M., Sater, M.R.A., Lagoudas, K.G., Blainey, P.C., Miller, L.G., McKinnell, J.A., Huang, S.S., Grad, Y.H. and Marttinen P. (2018). A Bayesian model of acquisition and clearance of bacterial colonization. ML4Health: Machine Learning for Health NeurIPS 2018 workshop. Online
Järvenpää, M., Gutmann, M.U., Pleska, A., Vehtari, A., and Marttinen, P. (2017). Efficient acquisition rules for model-based approximate Bayesian computation. Advances in Approximate Bayesian Inference NIPS 2017 Workshop. Online
Järvenpää, M., Gutmann, M.U., Vehtari, A., and Marttinen, P. (2017). Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria. NIPS 2017 Workshop on Machine Learning in Computational Biology. Workshop webpage
Lintusaari, J., Vuollekoski, H., Kangasrääsiö, A., Skytén, K., Järvenpää, M., Gutmann, M., Vehtari, A., Corander, J., and Kaski, S. (2017). ELFI: Engine for Likelihood Free Inference. ICML 2017 Workshop on Implicit Models. Online
Kangasrääsiö, A., Lintusaari, J., Skytén, K., Järvenpää, M., Vuollekoski, H., Gutmann, M., Vehtari, A., Corander, J., and Kaski, S. (2016). ELFI: Engine for Likelihood Free Inference. Advances in Approximate Bayesian Inference NIPS 2016 Workshop. Online
Last modified: 24 March 2022