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Higher Order Langevin Monte Carlo Algorithm
v1v2v3 (latest)

Higher Order Langevin Monte Carlo Algorithm

2 August 2018
Sotirios Sabanis
Ying Zhang
ArXiv (abs)PDFHTML

Papers citing "Higher Order Langevin Monte Carlo Algorithm"

15 / 15 papers shown
Title
Taming the Interacting Particle Langevin Algorithm: The Superlinear case
Taming the Interacting Particle Langevin Algorithm: The Superlinear case
Tim Johnston
Nikolaos Makras
Sotirios Sabanis
111
2
0
28 Mar 2024
Taming under isoperimetry
Taming under isoperimetry
Iosif Lytras
Sotirios Sabanis
77
4
0
15 Nov 2023
On the Posterior Distribution in Denoising: Application to Uncertainty
  Quantification
On the Posterior Distribution in Denoising: Application to Uncertainty Quantification
Hila Manor
T. Michaeli
UQCV
120
17
0
24 Sep 2023
Non-convex sampling for a mixture of locally smooth potentials
Non-convex sampling for a mixture of locally smooth potentials
D. Nguyen
82
0
0
31 Jan 2023
Kinetic Langevin MCMC Sampling Without Gradient Lipschitz Continuity --
  the Strongly Convex Case
Kinetic Langevin MCMC Sampling Without Gradient Lipschitz Continuity -- the Strongly Convex Case
Tim Johnston
Iosif Lytras
Sotirios Sabanis
79
9
0
19 Jan 2023
Gradient-based Adaptive Importance Samplers
Gradient-based Adaptive Importance Samplers
Victor Elvira
Émilie Chouzenoux
Ömer Deniz Akyildiz
Luca Martino
DiffM
101
10
0
19 Oct 2022
Optimized Population Monte Carlo
Optimized Population Monte Carlo
Victor Elvira
Émilie Chouzenoux
72
23
0
14 Apr 2022
Unadjusted Langevin algorithm for sampling a mixture of weakly smooth potentials
D. Nguyen
58
5
0
17 Dec 2021
Estimating High Order Gradients of the Data Distribution by Denoising
Estimating High Order Gradients of the Data Distribution by Denoising
Chenlin Meng
Yang Song
Wenzhe Li
Stefano Ermon
DiffM
85
46
0
08 Nov 2021
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient
  adaptive algorithms for neural networks
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks
Dong-Young Lim
Sotirios Sabanis
97
12
0
28 May 2021
On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint
  Sampling Method
On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method
Ye He
Krishnakumar Balasubramanian
Murat A. Erdogdu
66
35
0
06 Nov 2020
Taming neural networks with TUSLA: Non-convex learning via adaptive
  stochastic gradient Langevin algorithms
Taming neural networks with TUSLA: Non-convex learning via adaptive stochastic gradient Langevin algorithms
A. Lovas
Iosif Lytras
Miklós Rásonyi
Sotirios Sabanis
88
26
0
25 Jun 2020
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo
  under local conditions for nonconvex optimization
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization
Ömer Deniz Akyildiz
Sotirios Sabanis
97
17
0
13 Feb 2020
Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under
  local conditions in nonconvex optimization
Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization
Ying Zhang
Ömer Deniz Akyildiz
Theodoros Damoulas
Sotirios Sabanis
104
47
0
04 Oct 2019
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond
Xuechen Li
Denny Wu
Lester W. Mackey
Murat A. Erdogdu
96
71
0
19 Jun 2019
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