196 citations · 699 across the 80 of their papers we have counts for
7 papers · 1 filter
Deep State-Space Gaussian Processes
Zheng Zhao, Muhammad Emzir, Simo Särkkä
This paper is concerned with a state-space approach to deep Gaussian process (DGP) regression. We construct the DGP by hierarchically putting transformed Gaussian process (GP) prio…
Autonomous Tracking and State Estimation with Generalised Group Lasso
Rui Gao, Simo Särkkä, Rubén Claveria-Vega +1
We address the problem of autonomous tracking and state estimation for marine vessels, autonomous vehicles, and other dynamic signals under a (structured) sparsity assumption. The…
Variable Splitting Methods for Constrained State Estimation in Partially Observed Markov Processes
Rui Gao, Filip Tronarp, Simo Särkkä
In this paper, we propose a class of efficient, accurate, and general methods for solving state-estimation problems with equality and inequality constraints. The methods are based…
Continuous-Discrete Filtering and Smoothing on Submanifolds of Euclidean Space
Filip Tronarp, Simo Särkkä
In this paper the issue of filtering and smoothing in continuous discrete time is studied when the state variable evolves in some submanifold of Euclidean space, which may not have…
Bayesian ODE Solvers: The Maximum A Posteriori Estimate
Filip Tronarp, Simo Sarkka, Philipp Hennig
It has recently been established that the numerical solution of ordinary differential equations can be posed as a nonlinear Bayesian inference problem, which can be approximately s…
Enhancing Industrial X-ray Tomography by Data-Centric Statistical Methods
Jarkko Suuronen, Muhammad Emzir, Sari Lasanen +2
X-ray tomography has applications in various industrial fields such as sawmill industry, oil and gas industry, chemical engineering, and geotechnical engineering. In this article,…