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1605.01559
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High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm
5 May 2016
Alain Durmus
Eric Moulines
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Papers citing
"High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm"
50 / 79 papers shown
Title
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Diffusion at Absolute Zero: Langevin Sampling Using Successive Moreau Envelopes [conference paper]
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Alexander Falk
T. Pock
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Random Reshuffling for Stochastic Gradient Langevin Dynamics
Luke Shaw
Peter A. Whalley
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Non-geodesically-convex optimization in the Wasserstein space
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Hanlin Yu
Bernardo Williams
Petrus Mikkola
Marcelo Hartmann
Kai Puolamaki
Arto Klami
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Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics
Omar Chehab
Anna Korba
Austin Stromme
Adrien Vacher
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13 Oct 2024
On high-dimensional classification by sparse generalized Bayesian logistic regression
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19 Mar 2024
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d
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Joe Benton
Valentin De Bortoli
Arnaud Doucet
George Deligiannidis
DiffM
47
102
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07 Aug 2023
Contraction Rate Estimates of Stochastic Gradient Kinetic Langevin Integrators
B. Leimkuhler
Daniel Paulin
P. Whalley
31
5
0
14 Jun 2023
Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning
Shuxin Zheng
Jiyan He
Chang-Shu Liu
Yu Shi
Ziheng Lu
...
Peiran Jin
Chi Chen
Frank Noé
Haiguang Liu
Tie-Yan Liu
AI4CE
27
41
0
08 Jun 2023
When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm?
Yuansi Chen
Khashayar Gatmiry
99
15
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10 Apr 2023
Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models
Anant Raj
Umut Simsekli
Alessandro Rudi
DiffM
31
1
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30 Mar 2023
Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation
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F. R. Crucinio
Mark Girolami
Tim Johnston
Sotirios Sabanis
32
11
0
23 Mar 2023
Non-asymptotic analysis of Langevin-type Monte Carlo algorithms
Shogo H. Nakakita
19
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22 Mar 2023
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression
Avetik G. Karagulyan
Peter Richtárik
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31
6
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08 Mar 2023
Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation
Yue Xiang
Dongyao Zhu
Bowen Lei
Dongkuan Xu
Ruqi Zhang
26
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27 Feb 2023
Contraction and Convergence Rates for Discretized Kinetic Langevin Dynamics
B. Leimkuhler
Daniel Paulin
P. Whalley
32
16
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21 Feb 2023
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler
Sivakanth Gopi
Y. Lee
Daogao Liu
Ruoqi Shen
Kevin Tian
17
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13 Feb 2023
Non-convex sampling for a mixture of locally smooth potentials
D. Nguyen
33
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31 Jan 2023
Stochastic Langevin Monte Carlo for (weakly) log-concave posterior distributions
Marelys Crespo Navas
S. Gadat
X. Gendre
26
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08 Jan 2023
Unadjusted Hamiltonian MCMC with Stratified Monte Carlo Time Integration
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Milo Marsden
32
12
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20 Nov 2022
Jump-Diffusion Langevin Dynamics for Multimodal Posterior Sampling
Jacopo Guidolin
Vyacheslav Kungurtsev
Ondvrej Kuvzelka
BDL
18
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02 Nov 2022
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms
Vincent Plassier
Alain Durmus
Eric Moulines
FedML
21
6
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31 Oct 2022
Gaussian-Bernoulli RBMs Without Tears
Renjie Liao
Simon Kornblith
Mengye Ren
David J. Fleet
Geoffrey E. Hinton
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OOD
19
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19 Oct 2022
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling
Jason M. Altschuler
Kunal Talwar
38
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16 Oct 2022
Fisher information lower bounds for sampling
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Holden Lee
Chen Lu
49
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05 Oct 2022
Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition
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Avetik G. Karagulyan
Peter Richtárik
26
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01 Jun 2022
Optimized Population Monte Carlo
Victor Elvira
Émilie Chouzenoux
32
23
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14 Apr 2022
Metropolis Adjusted Langevin Trajectories: a robust alternative to Hamiltonian Monte Carlo
L. Riou-Durand
Jure Vogrinc
21
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26 Feb 2022
HMC and underdamped Langevin united in the unadjusted convex smooth case
Nicolai Gouraud
Pierre Le Bris
Adrien Majka
Pierre Monmarché
20
10
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02 Feb 2022
On Convergence of Federated Averaging Langevin Dynamics
Wei Deng
Qian Zhang
Yi Ma
Zhao-quan Song
Guang Lin
FedML
30
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09 Dec 2021
Bounding Wasserstein distance with couplings
N. Biswas
Lester W. Mackey
27
8
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06 Dec 2021
Statistical Finite Elements via Langevin Dynamics
Ömer Deniz Akyildiz
Connor Duffin
Sotirios Sabanis
Mark Girolami
36
11
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21 Oct 2021
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint
Y. Freund
Yi Ma
Tong Zhang
37
16
0
05 Oct 2021
Asymptotic bias of inexact Markov Chain Monte Carlo methods in high dimension
Alain Durmus
A. Eberle
24
19
0
02 Aug 2021
Uniform minorization condition and convergence bounds for discretizations of kinetic Langevin dynamics
Alain Durmus
Aurélien Enfroy
Eric Moulines
G. Stoltz
27
17
0
30 Jul 2021
Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo
Vyacheslav Kungurtsev
Adam D. Cobb
T. Javidi
Brian Jalaian
51
4
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15 Jul 2021
A Survey of Uncertainty in Deep Neural Networks
J. Gawlikowski
Cedrique Rovile Njieutcheu Tassi
Mohsin Ali
Jongseo Lee
Matthias Humt
...
R. Roscher
Muhammad Shahzad
Wen Yang
R. Bamler
Xiaoxiang Zhu
BDL
UQCV
OOD
41
1,111
0
07 Jul 2021
Schr{ö}dinger-F{ö}llmer Sampler: Sampling without Ergodicity
Jian Huang
Yuling Jiao
Lican Kang
Xu Liao
Jin Liu
Yanyan Liu
35
27
0
21 Jun 2021
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions
Y. Lee
Ruoqi Shen
Kevin Tian
16
20
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10 Jun 2021
On log-concave approximations of high-dimensional posterior measures and stability properties in non-linear inverse problems
Jan Bohr
Richard Nickl
13
17
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17 May 2021
Discrete sticky couplings of functional autoregressive processes
Alain Durmus
A. Eberle
Aurélien Enfroy
Arnaud Guillin
Pierre Monmarché
19
7
0
14 Apr 2021
Data-Free Likelihood-Informed Dimension Reduction of Bayesian Inverse Problems
Tiangang Cui
O. Zahm
20
22
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26 Feb 2021
Complexity of zigzag sampling algorithm for strongly log-concave distributions
Jianfeng Lu
Lihan Wang
13
6
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21 Dec 2020
On the cost of Bayesian posterior mean strategy for log-concave models
S. Gadat
Fabien Panloup
Clément Pellegrini
26
7
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08 Oct 2020
Convergence of Langevin Monte Carlo in Chi-Squared and Renyi Divergence
Murat A. Erdogdu
Rasa Hosseinzadeh
Matthew Shunshi Zhang
86
41
0
22 Jul 2020
Taming neural networks with TUSLA: Non-convex learning via adaptive stochastic gradient Langevin algorithms
A. Lovas
Iosif Lytras
Miklós Rásonyi
Sotirios Sabanis
15
25
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25 Jun 2020
A Non-Asymptotic Analysis for Stein Variational Gradient Descent
Anna Korba
Adil Salim
Michael Arbel
Giulia Luise
A. Gretton
15
76
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17 Jun 2020
On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness
Murat A. Erdogdu
Rasa Hosseinzadeh
6
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27 May 2020
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