Stochastic Gradient MCMC for State Space Models

22 October 2018

Papers citing "Stochastic Gradient MCMC for State Space Models"

10 / 10 papers shown

Title
Pigeonhole Stochastic Gradient Langevin Dynamics for Large Crossed Mixed Effects Models Xinyu Zhang Cheng Li 28 0 0 18 Dec 2022
Nonlinear System Identification: Learning while respecting physical models using a sequential Monte Carlo method A. Wigren Johan Wågberg Fredrik Lindsten A. Wills Thomas B. Schon 24 10 0 26 Oct 2022
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview, Implementation, and Applications Se Yoon Lee 21 18 0 28 Jan 2022
Divide-and-Conquer Bayesian Inference in Hidden Markov Models Chunlei Wang Sanvesh Srivastava 33 9 0 30 May 2021
Quantifying Uncertainty in Deep Spatiotemporal Forecasting Dongxian Wu Liyao (Mars) Gao X. Xiong Matteo Chinazzi Alessandro Vespignani Yi Ma Rose Yu AI4TS 13 68 0 25 May 2021
Variational Inference with Vine Copulas: An efficient Approach for Bayesian Computer Model Calibration Vojtech Kejzlar T. Maiti 16 6 0 28 Mar 2020
The Neural Moving Average Model for Scalable Variational Inference of State Space Models Tom Ryder D. Prangle Andrew Golightly Isaac Matthews BDL AI4TS 16 6 0 02 Oct 2019
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 22 135 0 16 Jul 2019
Measuring Sample Quality with Kernels Jackson Gorham Lester W. Mackey 86 223 0 06 Mar 2017
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators Changyou Chen Nan Ding Lawrence Carin 37 159 0 21 Oct 2016