20162019

Research output per year

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Research Output

  • 6 Conference contribution
  • 4 Article
  • 1 Editorial
  • 1 Doctoral Thesis
2019

Bayesian Predictive Inference and Feature Selection for High-Dimensional Data

Piironen, J., 2019, Aalto University. 190 p.

Research output: ThesisDoctoral ThesisCollection of Articles

Making Bayesian Predictive Models Interpretable: A Decision Theoretic Approach

Afrabandpey, H., Peltola, T., Piironen, J., Vehtari, A. & Kaski, S., 19 Oct 2019, (Submitted) Submitted. p. 1-16 16 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Pushing the Limits of Importance Sampling through Iterative Moment Matching

Paananen, T., Piironen, J., Burkner, P-C. & Vehtari, A., 20 Jun 2019, (Submitted) In : arXiv.org.

Research output: Contribution to journalArticleScientific

Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distribution

Paananen, T., Piironen, J., Andersen, M. & Vehtari, A., 16 Apr 2019, Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics. 10 p. (Proceedings of Machine Learning Research; vol. 89).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Open Access
File
13 Downloads (Pure)
2018

Iterative Supervised Principal Components

Piironen, J. & Vehtari, A., 2018, International Conference on Artificial Intelligence and Statistics, 9-11 April 2018, Playa Blanca, Lanzarote, Canary Islands. Storkey, A. & Perez-Cruz, F. (eds.). 9 p. (Proceedings of Machine Learning Research; vol. 84).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Open Access
File
12 Downloads (Pure)

Projective Inference in High-dimensional Problems: Prediction and Feature Selection

Piironen, J., Paasiniemi, M. & Vehtari, A., 2018, (Submitted) In : arXiv.org.

Research output: Contribution to journalArticleScientificpeer-review

2017

Comparison of Bayesian predictive methods for model selection

Piironen, J. & Vehtari, A., 2017, In : STATISTICS AND COMPUTING. 27, 3, p. 711-735 25 p.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
File
53 Citations (Scopus)
227 Downloads (Pure)

On the hyperprior choice for the global shrinkage parameter in the horseshoe prior

Piironen, J. & Vehtari, A., 2017, Proceedings of the 20th International Conference on Artificial Intelligence and Statistics. 9 p. (Proceedings of Machine Learning Research; vol. 54).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Open Access
File
9 Downloads (Pure)

Sparsity information and regularization in the horseshoe and other shrinkage priors

Piironen, J. & Vehtari, A., 2017, In : ELECTRONIC JOURNAL OF STATISTICS. 11, 2, p. 5018-5051

Research output: Contribution to journalArticleScientificpeer-review

Open Access
File
34 Citations (Scopus)
156 Downloads (Pure)

Uncertainty Quantification for the Horseshoe (with Discussion) comment

Piironen, J., Betancourt, M., Simpson, D. & Vehtari, A., Dec 2017, In : Bayesian Analysis. 12, 4, p. 1264-1266 3 p.

Research output: Contribution to journalEditorialScientificpeer-review

Open Access
File
5 Downloads (Pure)
2016

Automatic monotonicity detection for Gaussian Processes

Siivola, E., Piironen, J. & Vehtari, A., 2016, (Unpublished) Submitted.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Projection predictive model selection for Gaussian processes

Piironen, J. & Vehtari, A., 2016, 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP) . IEEE, (IEEE International Workshop on Machine Learning for Signal Processing).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

5 Citations (Scopus)