3 citations · 3 across the 2 of their papers we have counts for
3 papers
Segmentation of TCD Cerebral Blood Flow Velocity Recordings
Federico Wadehn, Andrea Fanelli, Thomas Heldt
A binary beat-by-beat classification algorithm for cerebral blood flow velocity (CBFV) recordings based on amplitude, spectral and morphological features is presented. The classifi…
On Sparsity by NUV-EM, Gaussian Message Passing, and Kalman Smoothing
Hans-Andrea Loeliger, Lukas Bruderer, Hampus Malmberg +2
Normal priors with unknown variance (NUV) have long been known to promote sparsity and to blend well with parameter learning by expectation maximization (EM). In this paper, we adv…
Sparse Learning of Markovian Population Models in Random Environments
Christoph Zechner, Federico Wadehn, Heinz Koeppl
Markovian population models are suitable abstractions to describe well-mixed interacting particle systems in situation where stochastic fluctuations are significant due to the invo…