Gaussian variational approximation for high-dimensional state space models

24 January 2018

Papers citing "Gaussian variational approximation for high-dimensional state space models"

22 / 22 papers shown

Title
Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold Hoang Phuc Hau Luu Hanlin Yu Bernardo Williams Marcelo Hartmann Arto Klami DRL 38 0 0 03 Oct 2024
Efficient, Multimodal, and Derivative-Free Bayesian Inference With Fisher-Rao Gradient Flows Yifan Chen Daniel Zhengyu Huang Jiaoyang Huang Sebastian Reich Andrew M. Stuart 48 5 0 25 Jun 2024
Provably Scalable Black-Box Variational Inference with Structured Variational Families Joohwan Ko Kyurae Kim W. Kim Jacob R. Gardner BDL 30 2 0 19 Jan 2024
ABC-based Forecasting in State Space Models Chaya Weerasinghe Rubén Loaiza-Maya G. Martin David T. Frazier 16 1 0 02 Nov 2023
Sampling via Gradient Flows in the Space of Probability Measures Yifan Chen Daniel Zhengyu Huang Jiaoyang Huang Sebastian Reich Andrew M. Stuart 30 13 0 05 Oct 2023
Stochastic Variational Inference for GARCH Models Hanwen Xuan Luca Maestrini F. Chen Clara Grazian 17 2 0 29 Aug 2023
Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent Tianle Liu Promit Ghosal Krishnakumar Balasubramanian Natesh S. Pillai 24 9 0 23 May 2023
Accelerate Langevin Sampling with Birth-Death process and Exploration Component Lezhi Tan Jianfeng Lu 17 3 0 06 May 2023
Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space Michael Diao Krishnakumar Balasubramanian Sinho Chewi Adil Salim BDL 24 20 0 10 Apr 2023
Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance Yifan Chen Daniel Zhengyu Huang Jiaoyang Huang Sebastian Reich Andrew M. Stuart 11 17 0 21 Feb 2023
Structured variational approximations with skew normal decomposable graphical models Roberto Salomone Xue Yu David J. Nott Robert Kohn 19 2 0 07 Feb 2023
Federated Variational Inference Methods for Structured Latent Variable Models Conor Hassan Roberto Salomone Kerrie Mengersen BDL FedML 21 4 0 07 Feb 2023
Efficient variational approximations for state space models Rubén Loaiza-Maya D. Nibbering 6 1 0 20 Oct 2022
Separation of Scales and a Thermodynamic Description of Feature Learning in Some CNNs Inbar Seroussi Gadi Naveh Z. Ringel 30 50 0 31 Dec 2021
Approximating Bayes in the 21st Century G. Martin David T. Frazier Christian P. Robert 36 26 0 20 Dec 2021
Variational Bayes in State Space Models: Inferential and Predictive Accuracy David T. Frazier Rubén Loaiza-Maya G. Martin 11 13 0 23 Jun 2021
Variational Approximation of Factor Stochastic Volatility Models David Gunawan Robert Kohn David J. Nott 9 7 0 13 Oct 2020
Computing Bayes: Bayesian Computation from 1763 to the 21st Century G. Martin David T. Frazier Christian P. Robert 40 17 0 14 Apr 2020
High-dimensional copula variational approximation through transformation M. Smith Rubén Loaiza-Maya David J. Nott 17 33 0 16 Apr 2019
Comparison of Deep Neural Networks and Deep Hierarchical Models for Spatio-Temporal Data C. Wikle BDL 35 19 0 22 Feb 2019
Variance reduction properties of the reparameterization trick Ming Xu M. Quiroz Robert Kohn S. Sisson AAML 16 65 0 27 Sep 2018
Black-box Variational Inference for Stochastic Differential Equations Tom Ryder Andrew Golightly A. Mcgough D. Prangle 14 57 0 09 Feb 2018