ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1503.08650
  4. Cited By
Comparison of Bayesian predictive methods for model selection

Comparison of Bayesian predictive methods for model selection

30 March 2015
Juho Piironen
Aki Vehtari
ArXivPDFHTML

Papers citing "Comparison of Bayesian predictive methods for model selection"

16 / 16 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
A Practitioner's Guide to Bayesian Inference in Pharmacometrics using
  Pumas
A Practitioner's Guide to Bayesian Inference in Pharmacometrics using Pumas
Mohamed Tarek
J. Storópoli
Casey B. Davis
C. Elrod
Julius Krumbiegel
Chris Rackauckas
V. Ivaturi
GP
15
3
0
31 Mar 2023
A review of predictive uncertainty estimation with machine learning
A review of predictive uncertainty estimation with machine learning
Hristos Tyralis
Georgia Papacharalampous
UD
UQCV
51
43
0
17 Sep 2022
Forecasting: theory and practice
Forecasting: theory and practice
F. Petropoulos
D. Apiletti
Vassilios Assimakopoulos
M. Z. Babai
Devon K. Barrow
...
J. Arenas
Xiaoqian Wang
R. L. Winkler
Alisa Yusupova
F. Ziel
AI4TS
36
363
0
04 Dec 2020
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
16
0
0
27 May 2020
Marginal likelihood computation for model selection and hypothesis
  testing: an extensive review
Marginal likelihood computation for model selection and hypothesis testing: an extensive review
F. Llorente
Luca Martino
D. Delgado
J. Lopez-Santiago
19
83
0
17 May 2020
Decision-Making Under Uncertainty in Research Synthesis: Designing for
  the Garden of Forking Paths
Decision-Making Under Uncertainty in Research Synthesis: Designing for the Garden of Forking Paths
Alex Kale
Matthew Kay
Jessica Hullman
14
40
0
09 Jan 2019
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
Projective Inference in High-dimensional Problems: Prediction and
  Feature Selection
Projective Inference in High-dimensional Problems: Prediction and Feature Selection
Juho Piironen
Markus Paasiniemi
Aki Vehtari
16
94
0
04 Oct 2018
The Median Probability Model and Correlated Variables
The Median Probability Model and Correlated Variables
Marilena Barbieri
J. Berger
E. George
Veronika Rockova
11
43
0
22 Jul 2018
Bayesian comparison of latent variable models: Conditional vs marginal
  likelihoods
Bayesian comparison of latent variable models: Conditional vs marginal likelihoods
Edgar C. Merkle
Daniel Furr
S. Rabe-Hesketh
10
71
0
13 Feb 2018
Model Averaging and its Use in Economics
Model Averaging and its Use in Economics
M. Steel
MoMe
14
238
0
24 Sep 2017
Uncertainty quantification for the horseshoe
Uncertainty quantification for the horseshoe
S. V. D. Pas
Botond Szabó
A. van der Vaart
25
71
0
07 Jul 2016
Mode jumping MCMC for Bayesian variable selection in GLMM
Mode jumping MCMC for Bayesian variable selection in GLMM
A. Hubin
G. Storvik
20
28
0
21 Apr 2016
Fast methods for training Gaussian processes on large data sets
Fast methods for training Gaussian processes on large data sets
C. Moore
A. J. Chua
C. Berry
J. Gair
GP
14
41
0
05 Apr 2016
Practical Bayesian model evaluation using leave-one-out cross-validation
  and WAIC
Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC
Aki Vehtari
Andrew Gelman
Jonah Gabry
20
3,983
0
16 Jul 2015
1