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Convergence rates for optimised adaptive importance samplers

Convergence rates for optimised adaptive importance samplers

28 March 2019
Ömer Deniz Akyildiz
Joaquín Míguez
ArXivPDFHTML

Papers citing "Convergence rates for optimised adaptive importance samplers"

13 / 13 papers shown
Title
Quantification of Uncertainty with Adversarial Models
Quantification of Uncertainty with Adversarial Models
Kajetan Schweighofer
L. Aichberger
Mykyta Ielanskyi
G. Klambauer
Sepp Hochreiter
UQCV
42
14
0
06 Jul 2023
Regularized Rényi divergence minimization through Bregman proximal
  gradient algorithms
Regularized Rényi divergence minimization through Bregman proximal gradient algorithms
Thomas Guilmeau
Émilie Chouzenoux
Victor Elvira
34
3
0
09 Nov 2022
Efficient Bayes Inference in Neural Networks through Adaptive Importance
  Sampling
Efficient Bayes Inference in Neural Networks through Adaptive Importance Sampling
Yunshi Huang
Émilie Chouzenoux
Victor Elvira
J. Pesquet
BDL
26
5
0
03 Oct 2022
Optimized Population Monte Carlo
Optimized Population Monte Carlo
Victor Elvira
Émilie Chouzenoux
32
23
0
14 Apr 2022
Global convergence of optimized adaptive importance samplers
Global convergence of optimized adaptive importance samplers
Ömer Deniz Akyildiz
30
7
0
02 Jan 2022
MCMC-driven importance samplers
MCMC-driven importance samplers
F. Llorente
E. Curbelo
Luca Martino
Victor Elvira
D. Delgado
32
11
0
06 May 2021
NEO: Non Equilibrium Sampling on the Orbit of a Deterministic Transform
NEO: Non Equilibrium Sampling on the Orbit of a Deterministic Transform
Achille Thin
Yazid Janati
Sylvain Le Corff
Charles Ollion
Arnaud Doucet
Alain Durmus
Eric Moulines
C. Robert
32
7
0
17 Mar 2021
Advances in Importance Sampling
Advances in Importance Sampling
Victor Elvira
Luca Martino
AI4TS
45
103
0
10 Feb 2021
Context-aware surrogate modeling for balancing approximation and
  sampling costs in multi-fidelity importance sampling and Bayesian inverse
  problems
Context-aware surrogate modeling for balancing approximation and sampling costs in multi-fidelity importance sampling and Bayesian inverse problems
Terrence Alsup
Benjamin Peherstorfer
35
11
0
22 Oct 2020
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
34
19
0
20 Oct 2020
Bayesian Update with Importance Sampling: Required Sample Size
Bayesian Update with Importance Sampling: Required Sample Size
D. Sanz-Alonso
Zijian Wang
14
6
0
22 Sep 2020
Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural
  networks: perspectives from the theory of controlled diffusions and measures
  on path space
Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space
Nikolas Nusken
Lorenz Richter
AI4CE
19
103
0
11 May 2020
Stochastic Gradient Descent for Non-smooth Optimization: Convergence
  Results and Optimal Averaging Schemes
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes
Ohad Shamir
Tong Zhang
101
571
0
08 Dec 2012
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