2 citations · 2 across the 2 of their papers we have counts for
4 papers
Motion-Enabled Tomography of Gaussian-Mixture Particles under Unknown Rigid-Body Motion with Parabolic Trajectories
Daniel Burrows, Can Evren Yarman, Ozan Öktem
Reconstructing objects with unknown position and/or orientation arises in applications spanning geology to cryo-ET. When the relative motion between the object and the sensing appa…
Gaussian mixture model decomposition of multivariate signals
Gustav Zickert, Can Evren Yarman
We propose a greedy variational method for decomposing a non-negative multivariate signal as a weighted sum of Gaussians, which, borrowing the terminology from statistics, we refer…
Approximating fractional derivative of the Gaussian function and Dawson's integral
Can Evren Yarman
A new method for approximating fractional derivatives of the Gaussian function and Dawson's integral are presented. Unlike previous approaches, which are dominantly based on some d…
Sampling for approximating -limited functions
Can Evren Yarman
-limited functions are multivariate generalization of band-limited functions whose Fourier transforms are supported within a compact region . In this wor…