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2108.00490
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A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC
3 January 2025
F. Llorente
Luca Martino
Jesse Read
D. Delgado
OffRL
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Papers citing
"A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC"
11 / 11 papers shown
Title
Binary classification based Monte Carlo simulation
Elouan Argouarc'h
F. Desbouvries
20
0
0
29 Jul 2023
Deep Metric Tensor Regularized Policy Gradient
Gang Chen
Victoria Huang
26
0
0
18 May 2023
A Survey of Quantum Alternatives to Randomized Algorithms: Monte Carlo Integration and Beyond
P. Intallura
Georgios Korpas
Sudeepto Chakraborty
Vyacheslav Kungurtsev
Jakub Mareˇcek
14
11
0
08 Mar 2023
ISFL: Federated Learning for Non-i.i.d. Data with Local Importance Sampling
Zheqi Zhu
Yuchen Shi
Pingyi Fan
Chenghui Peng
Khaled B. Letaief
FedML
25
8
0
05 Oct 2022
CAMEO: Curiosity Augmented Metropolis for Exploratory Optimal Policies
Mohamed Alami Chehboune
F. Llorente
Rim Kaddah
Luca Martino
Jesse Read
21
0
0
19 May 2022
Optimality in Noisy Importance Sampling
F. Llorente
Luca Martino
Jesse Read
D. Delgado
39
5
0
07 Jan 2022
Revisiting Bayesian Autoencoders with MCMC
Rohitash Chandra
Mahir Jain
Manavendra Maharana
P. Krivitsky
UQCV
BDL
29
17
0
13 Apr 2021
A Two Stage Adaptive Metropolis Algorithm
Anirban Mondal
Kai-Li Yin
A. Mandal
22
1
0
01 Jan 2021
Rate-optimal refinement strategies for local approximation MCMC
Andrew D. Davis
Youssef Marzouk
Aaron Smith
Natesh Pillai
11
10
0
29 May 2020
Stability of Noisy Metropolis-Hastings
F. Medina-Aguayo
Anthony Lee
Gareth O. Roberts
59
41
0
24 Mar 2015
Local Gaussian process approximation for large computer experiments
R. Gramacy
D. Apley
124
391
0
02 Mar 2013
1