Preprints

Mikkola, P., Acerbi, L., Klami, A. (2025). Score-Based Density Estimation from Pairwise Comparisons. arXiv preprint. Preprint.

Selected publications

Mikkola, P., Acerbi, L., Klami, A. (2024). Preferential Normalizing Flows. Advances in Neural Information Processing Systems - Volume 37. NeurIPS’24. Proceedings, Preprint, Code.

Mikkola, P., Todorović, M., Järvi, J., Rinke, P., Kaski, S. (2020). Projective Preferential Bayesian Optimization. In Proceedings of the 37th International Conference on Machine Learning - Volume 119. ICML’20. Proceedings, Preprint, Code.

Mikkola, P., Martinelli, J., Filstroff, L., Kaski, S. (2023). Multi-Fidelity Bayesian Optimization with Unreliable Information Sources. In Proceedings of the 26th International Conference on Artificial Intelligence and Statistics - Volume 206. AISTATS’23. Proceedings, Preprint, Code.

Mikkola, P., Martin, O. A., Chandramouli, S., Hartmann, M., Abril Pla, O., Thomas, O., Pesonen, P., Corander, J., Vehtari, A., Kaski, S., Bürkner, P-C., Klami, A. (2024). Prior knowledge elicitation: The past, present, and future. Bayesian Analysis. Publication, Preprint.

Chengkun, L., Huggins, B., Mikkola, P., Acerbi, L. (2025). Normalizing Flow Regression for Bayesian Inference with Offline Likelihood Evaluations. 7th Symposium on Advances in Approximate Bayesian Inference - Proceedings Track. AABI’25. Proceedings.

Workshops

Tiihonen, A., Filstroff, L., Mikkola, P., Lehto, E., Kaski, S., Todorović, M., Rinke, P. (2022). More trustworthy Bayesian optimization of materials properties by adding human into the loop. NeurIPS 2022 Workshop AI4Mat. Workshop.

Huang, D., Filstroff, L., Mikkola, P., Zheng, R., Kaski, S. (2023). Augmenting Bayesian Optimization with Preference-based Expert Feedback. ICML 2023 Workshop “The Many Facets of Preference-Based Learning”. Workshop, Preprint.