High-dimensional Gaussian sampling: a review and a unifying approach based on a stochastic proximal point algorithm

4 October 2020

Papers citing "High-dimensional Gaussian sampling: a review and a unifying approach based on a stochastic proximal point algorithm"

9 / 9 papers shown

Title
Streamlining Prediction in Bayesian Deep Learning Rui Li Marcus Klasson Arno Solin Martin Trapp UQCV BDL 97 2 0 27 Nov 2024
Batched Bayesian optimization by maximizing the probability of including the optimum Jenna C. Fromer Runzhong Wang Mrunali Manjrekar Austin Tripp José Miguel Hernández-Lobato Connor W. Coley 47 0 0 08 Oct 2024
Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors Zihui Wu Yu Sun Yifan Chen Bingliang Zhang Yisong Yue Katherine L. Bouman DiffM 34 20 0 29 May 2024
Plug-and-Play split Gibbs sampler: embedding deep generative priors in Bayesian inference Florentin Coeurdoux N. Dobigeon P. Chainais 27 15 0 21 Apr 2023
Leveraging joint sparsity in hierarchical Bayesian learning J. Glaubitz Anne Gelb 24 5 0 29 Mar 2023
Personalised Federated Learning On Heterogeneous Feature Spaces A. Rakotomamonjy Maxime Vono H. M. Ruiz L. Ralaivola FedML 18 8 0 26 Jan 2023
Hamiltonian Monte Carlo for efficient Gaussian sampling: long and random steps Simon Apers S. Gribling Dániel Szilágyi 36 10 0 26 Sep 2022
Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process Priors Wanyu Du Jianqiao Zhao Liwei Wang Yangfeng Ji BDL 27 15 0 04 Apr 2022
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting Maxime Vono Daniel Paulin Arnaud Doucet 24 37 0 23 May 2019