49 citations · 104 across the 19 of their papers we have counts for
20 papers
Kolmogorov-Arnold Networks for Spatially Independent Multispectral Land Classification
Katherine L. Bauer, Teemu Harkonen, Simo Sarkka +1
Land classification from satellite imagery is important for land management, environmental monitoring, and urban planning. Machine learning methods such as random forests and multi…
Estimation of log-Gaussian gamma processes with iterated posterior linearization and Hamiltonian Monte Carlo
Teemu Härkönen, Simo Särkkä
Stochastic processes are a flexible and widely used family of models for statistical modeling. While stochastic processes offer attractive properties such as inclusion of uncertain…
Recursive Entropic Variational Inference for Nonlinear State-Space Models
Hany Abdulsamad, Ángel F. García-Fernández, Simo Särkkä
We present a class of algorithms for state estimation in nonlinear, non-Gaussian state-space models. Our approach is based on a variational Lagrangian formulation that casts Bayesi…
Gaussian-Based Parametric Bijections For Automatic Projection Filters
Muhammad F. Emzir, Zheng Zhao, Lahouari Cheded +1
The automatic projection filter is a recently developed numerical method for projection filtering that leverages sparse-grid integration and automatic differentiation. However, its…
Online Pole Segmentation on Range Images for Long-term LiDAR Localization in Urban Environments
Hao Dong, Xieyuanli Chen, Simo Särkkä +1
Robust and accurate localization is a basic requirement for mobile autonomous systems. Pole-like objects, such as traffic signs, poles, and lamps are frequently used landmarks for…
The Coupled Rejection Sampler
Adrien Corenflos, Simo Särkkä
We propose a coupled rejection-sampling method for sampling from couplings of arbitrary distributions. The method relies on accepting or rejecting coupled samples coming from domin…