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

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

4 October 2018
Juho Piironen
Markus Paasiniemi
Aki Vehtari
ArXivPDFHTML

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

4 / 4 papers shown
Title
The ARR2 prior: flexible predictive prior definition for Bayesian
  auto-regressions
The ARR2 prior: flexible predictive prior definition for Bayesian auto-regressions
David Kohns
Noa Kallioinen
Yann McLatchie
Aki Vehtari
20
0
0
30 May 2024
Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference
Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference
Philipp Reiser
Javier Enrique Aguilar
A. Guthke
Paul-Christian Burkner
36
2
0
08 Dec 2023
Bayesian model selection in the $\mathcal{M}$-open setting --
  Approximate posterior inference and probability-proportional-to-size
  subsampling for efficient large-scale leave-one-out cross-validation
Bayesian model selection in the M\mathcal{M}M-open setting -- Approximate posterior inference and probability-proportional-to-size subsampling for efficient large-scale leave-one-out cross-validation
Riko Kelter
19
0
0
27 May 2020
Limitations of "Limitations of Bayesian leave-one-out cross-validation
  for model selection"
Limitations of "Limitations of Bayesian leave-one-out cross-validation for model selection"
Aki Vehtari
Daniel P. Simpson
Yuling Yao
Andrew Gelman
11
52
0
12 Oct 2018
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