484 citations · 486 across the 2 of their papers we have counts for
5 papers
Using reference models in variable selection
Federico Pavone, Juho Piironen, Paul-Christian Bürkner +1
Variable selection, or more generally, model reduction is an important aspect of the statistical workflow aiming to provide insights from data. In this paper, we discuss and demons…
A Decision-Theoretic Approach for Model Interpretability in Bayesian Framework
Homayun Afrabandpey, Tomi Peltola, Juho Piironen +2
A salient approach to interpretable machine learning is to restrict modeling to simple models. In the Bayesian framework, this can be pursued by restricting the model structure and…
Implicitly Adaptive Importance Sampling
Topi Paananen, Juho Piironen, Paul-Christian Bürkner +1
Adaptive importance sampling is a class of techniques for finding good proposal distributions for importance sampling. Often the proposal distributions are standard probability dis…
Projective Inference in High-dimensional Problems: Prediction and Feature Selection
Juho Piironen, Markus Paasiniemi, Aki Vehtari
This paper discusses predictive inference and feature selection for generalized linear models with scarce but high-dimensional data. We argue that in many cases one can benefit fro…
Sparsity information and regularization in the horseshoe and other shrinkage priors
Juho Piironen, Aki Vehtari
The horseshoe prior has proven to be a noteworthy alternative for sparse Bayesian estimation, but has previously suffered from two problems. First, there has been no systematic way…