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. 2005.08334
  4. Cited By
Marginal likelihood computation for model selection and hypothesis
  testing: an extensive review

Marginal likelihood computation for model selection and hypothesis testing: an extensive review

17 May 2020
F. Llorente
Luca Martino
D. Delgado
J. Lopez-Santiago
ArXivPDFHTML

Papers citing "Marginal likelihood computation for model selection and hypothesis testing: an extensive review"

15 / 15 papers shown
Title
Adaptive posterior distributions for uncertainty analysis of covariance matrices in Bayesian inversion problems for multioutput signals
E. Curbelo
Luca Martino
F. Llorente
D. Delgado-Gomez
40
1
0
03 Jan 2025
Liouville Flow Importance Sampler
Liouville Flow Importance Sampler
Yifeng Tian
Nishant Panda
Yen Ting Lin
28
8
0
03 May 2024
Dynamic Online Ensembles of Basis Expansions
Dynamic Online Ensembles of Basis Expansions
Daniel Waxman
Petar M. Djurić
20
3
0
02 May 2024
Spectral information criterion for automatic elbow detection
Spectral information criterion for automatic elbow detection
Luca Martino
Roberto San Millán-Castillo
E. Morgado
18
9
0
17 Aug 2023
Sparse Bayesian Estimation of Parameters in Linear-Gaussian State-Space
  Models
Sparse Bayesian Estimation of Parameters in Linear-Gaussian State-Space Models
Benjamin Cox
Victor Elvira
20
10
0
20 Jun 2023
Computing Bayes: From Then 'Til Now'
Computing Bayes: From Then 'Til Now'
G. Martin
David T. Frazier
Christian P. Robert
20
15
0
01 Aug 2022
Nested sampling for physical scientists
Nested sampling for physical scientists
G. Ashton
N. Bernstein
Johannes Buchner
Xi Chen
Gábor Csányi
...
Leah F. South
J. Veitch
Philipp Wacker
D. Wales
David Yallup
31
76
0
31 May 2022
Marginal and Joint Cross-Entropies & Predictives for Online Bayesian
  Inference, Active Learning, and Active Sampling
Marginal and Joint Cross-Entropies & Predictives for Online Bayesian Inference, Active Learning, and Active Sampling
Andreas Kirsch
Jannik Kossen
Y. Gal
UQCV
BDL
34
3
0
18 May 2022
Bayesian Model Selection, the Marginal Likelihood, and Generalization
Bayesian Model Selection, the Marginal Likelihood, and Generalization
Sanae Lotfi
Pavel Izmailov
Gregory W. Benton
Micah Goldblum
A. Wilson
UQCV
BDL
45
56
0
23 Feb 2022
Optimality in Noisy Importance Sampling
Optimality in Noisy Importance Sampling
F. Llorente
Luca Martino
Jesse Read
D. Delgado
17
5
0
07 Jan 2022
Approximating Bayes in the 21st Century
Approximating Bayes in the 21st Century
G. Martin
David T. Frazier
Christian P. Robert
27
26
0
20 Dec 2021
Priors in Bayesian Deep Learning: A Review
Priors in Bayesian Deep Learning: A Review
Vincent Fortuin
UQCV
BDL
22
124
0
14 May 2021
MCMC-driven importance samplers
MCMC-driven importance samplers
F. Llorente
E. Curbelo
Luca Martino
Victor Elvira
D. Delgado
19
11
0
06 May 2021
Deep Importance Sampling based on Regression for Model Inversion and
  Emulation
Deep Importance Sampling based on Regression for Model Inversion and Emulation
F. Llorente
Luca Martino
D. Delgado
G. Camps-Valls
10
19
0
20 Oct 2020
Improved Adaptive Rejection Metropolis Sampling Algorithms
Improved Adaptive Rejection Metropolis Sampling Algorithms
Luca Martino
Jesse Read
D. Luengo
35
85
0
24 May 2012
1