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A Survey of Monte Carlo Methods for Parameter Estimation

A Survey of Monte Carlo Methods for Parameter Estimation

25 July 2021
D. Luengo
Luca Martino
M. Bugallo
Victor Elvira
S. Särkkä
ArXivPDFHTML

Papers citing "A Survey of Monte Carlo Methods for Parameter Estimation"

16 / 16 papers shown
Title
CoCoAFusE: Beyond Mixtures of Experts via Model Fusion
CoCoAFusE: Beyond Mixtures of Experts via Model Fusion
Aurelio Raffa Ugolini
M. Tanelli
Valentina Breschi
MoE
17
0
0
02 May 2025
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
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC
F. Llorente
Luca Martino
Jesse Read
D. Delgado
OffRL
58
13
0
03 Jan 2025
Accelerating Convergence of Stein Variational Gradient Descent via Deep
  Unfolding
Accelerating Convergence of Stein Variational Gradient Descent via Deep Unfolding
Yuya Kawamura
Satoshi Takabe
BDL
24
0
0
23 Feb 2024
Designing Proposal Distributions for Particle Filters using Integrated
  Nested Laplace Approximation
Designing Proposal Distributions for Particle Filters using Integrated Nested Laplace Approximation
A. Amri
11
1
0
05 May 2023
Optimality in Noisy Importance Sampling
Optimality in Noisy Importance Sampling
F. Llorente
Luca Martino
Jesse Read
D. Delgado
12
5
0
07 Jan 2022
Unrolled Variational Bayesian Algorithm for Image Blind Deconvolution
Unrolled Variational Bayesian Algorithm for Image Blind Deconvolution
Yunshi Huang
Émilie Chouzenoux
J. Pesquet
BDL
11
12
0
14 Oct 2021
Advances in Importance Sampling
Advances in Importance Sampling
Victor Elvira
Luca Martino
AI4TS
23
102
0
10 Feb 2021
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
13
80
0
17 May 2020
Measuring Sample Quality with Kernels
Measuring Sample Quality with Kernels
Jackson Gorham
Lester W. Mackey
78
221
0
06 Mar 2017
A Kernel Test of Goodness of Fit
A Kernel Test of Goodness of Fit
Kacper P. Chwialkowski
Heiko Strathmann
A. Gretton
BDL
94
324
0
09 Feb 2016
Gradient Importance Sampling
Gradient Importance Sampling
Ingmar Schuster
14
24
0
21 Jul 2015
Stability of Noisy Metropolis-Hastings
Stability of Noisy Metropolis-Hastings
F. Medina-Aguayo
Anthony Lee
Gareth O. Roberts
46
41
0
24 Mar 2015
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
132
3,260
0
09 Jun 2012
Coupled MCMC with a randomized acceptance probability
Coupled MCMC with a randomized acceptance probability
Geoff K. Nicholls
C. Fox
Alexis Muir Watt
37
39
0
30 May 2012
Improved Adaptive Rejection Metropolis Sampling Algorithms
Improved Adaptive Rejection Metropolis Sampling Algorithms
Luca Martino
Jesse Read
D. Luengo
35
85
0
24 May 2012
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