196 citations · 699 across the 80 of their papers we have counts for
9 papers · 1 filter
On the Convergence of Numerical Integration as a Finite Matrix Approximation to Multiplication Operator
Juha Sarmavuori, Simo Särkkä
We study the convergence of a family of numerical integration methods where the numerical integral is formulated as a finite matrix approximation to a multiplication operator. For…
Kernel-based interpolation at approximate Fekete points
Toni Karvonen, Simo Särkkä, Ken'ichiro Tanaka
We construct approximate Fekete point sets for kernel-based interpolation by maximising the determinant of a kernel Gram matrix obtained via truncation of an orthonormal expansion…
Automated Polysomnography Analysis for Detection of Non-Apneic and Non-Hypopneic Arousals using Feature Engineering and a Bidirectional LSTM Network
Ali Bahrami Rad, Morteza Zabihi, Zheng Zhao +3
Objective: The aim of this study is to develop an automated classification algorithm for polysomnography (PSG) recordings to detect non-apneic and non-hypopneic arousals. Our parti…
Dynamic 3D Tomographic X-ray Data of Ladybug
Juliaana Juurakko, Zenith Purisha, Simo Särkkä
This is the documentation of the 3D dynamic tomographic X-ray (CT) data of a ladybug. The open data set is available https://zenodo.org/record/3375488#.XV_T3vxS9oA and can be freel…
The Use of Gaussian Processes in System Identification
Simo Särkkä
Gaussian processes are used in machine learning to learn input-output mappings from observed data. Gaussian process regression is based on imposing a Gaussian process prior on the…
Worst-case optimal approximation with increasingly flat Gaussian kernels
Toni Karvonen, Simo Särkkä
We study worst-case optimal approximation of positive linear functionals in reproducing kernel Hilbert spaces induced by increasingly flat Gaussian kernels. This provides a new per…