Exactly Sparse Gaussian Variational Inference with Application to
Derivative-Free Batch Nonlinear State Estimation

v1v2 (latest)

Exactly Sparse Gaussian Variational Inference with Application to Derivative-Free Batch Nonlinear State Estimation

9 November 2019

Timothy D. Barfoot

James R. Forbes

ArXiv (abs)PDF HTML

Papers citing "Exactly Sparse Gaussian Variational Inference with Application to Derivative-Free Batch Nonlinear State Estimation"

8 / 8 papers shown

Title
Continuous-Time State Estimation Methods in Robotics: A Survey William Talbot Julian Nubert Turcan Tuna Cesar Cadena Frederike Dumbgen J. Tordesillas Timothy D. Barfoot Marco Hutter 123 11 0 06 Nov 2024
Multivariate Gaussian Variational Inference by Natural Gradient Descent Timothy D. Barfoot 42 13 0 27 Jan 2020
FutureMapping 2: Gaussian Belief Propagation for Spatial AI Andrew J. Davison Joseph Ortiz 170 45 0 30 Oct 2019
Continuous-Time Gaussian Process Motion Planning via Probabilistic Inference Mustafa Mukadam Jing Dong Xinyan Yan F. Dellaert Byron Boots GP 64 216 0 24 Jul 2017
Sigma-Point Filtering and Smoothing Based Parameter Estimation in Nonlinear Dynamic Systems Juho Kokkala Arno Solin Simo Särkkä 32 61 0 23 Apr 2015
On the relation between Gaussian process quadratures and sigma-point methods Simo Särkkä Jouni Hartikainen Lennart Svensson Fredrik Sandblom 77 42 0 22 Apr 2015
Batch Nonlinear Continuous-Time Trajectory Estimation as Exactly Sparse Gaussian Process Regression S. Anderson Timothy D. Barfoot Chi Hay Tong Simo Särkkä 61 87 0 01 Dec 2014
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 265 2,628 0 29 Jun 2012

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.