| Bayesian optimization with shape constraints M Jauch, V Peña NeurIPS Bayesian Optimization Workshop 2016, 2016 | 13 | 2016 |
| Designing alternative splicing RNA-seq studies. Beyond generic guidelines C Stephan-Otto Attolini, V Peña, D Rossell Bioinformatics 31 (22), 3631-3637, 2015 | 13 | 2015 |
| Bayesian bootstraps for massive data AF Barrientos, V Peña | 9 | 2020 |
| On the prevalence of information inconsistency in normal linear models J Mulder, JO Berger, V Peña, MJ Bayarri Test 30, 103-132, 2021 | 7 | 2021 |
| Differentially private methods for managing model uncertainty in linear regression models V Peña, AF Barrientos arXiv preprint arXiv:2109.03949, 2021 | 6 | 2021 |
| Bayesian variable selection in high dimensional problems without assumptions on prior model probabilities JO Berger, G Garcia-Donato, MA Martinez-Beneito, V Peña arXiv preprint arXiv:1607.02993, 2016 | 6 | 2016 |
| On the Relationship between Uhlig Extended and beta‐Bartlett Processes V Peña, K Irie Journal of Time Series Analysis 43 (1), 147-153, 2022 | 5 | 2022 |
| A note on recent criticisms to Birnbaum's theorem V Peña, JO Berger arXiv preprint arXiv:1711.08093, 2017 | 4 | 2017 |
| Differentially Private Hypothesis Testing with the Subsampled and Aggregated Randomized Response Mechanism V Peña, AF Barrientos https://arxiv.org/abs/2208.06803, 2022 | 3 | 2022 |
| Restricted type II maximum likelihood priors on regression coefficients V Peña, JO Berger | 3 | 2020 |
| Mixture representations for likelihood ratio ordered distributions M Jauch, AF Barrientos, V Peña, DS Matteson arXiv preprint arXiv:2110.04852, 2021 | 1 | 2021 |
