8 citations · 23 across the 5 of their papers we have counts for
5 papers
General Pruning Criteria for Fast SBL
Jakob Möderl, Erik Leitinger, Bernard Henri Fleury
Sparse Bayesian learning (SBL) associates to each weight in the underlying linear model a hyperparameter by assuming that each weight is Gaussian distributed with zero mean and pre…
"UWBCarGraz" Dataset for Car Occupancy Detection using Ultra-Wideband Radar
Jakob Möderl, Stefan Posch, Franz Pernkopf +1
We present a data-driven car occupancy detection algorithm using ultra-wideband radar based on the ResNet architecture. The algorithm is trained on a dataset of channel impulse res…
Fast Variational Block-Sparse Bayesian Learning
Jakob Möderl, Erik Leitinger, Bernard H. Fleury +2
We propose a variational Bayesian (VB) implementation of block-sparse Bayesian learning (BSBL) to compute proxy probability density functions (PDFs) that approximate the posterior…
Variational Inference of Structured Line Spectra Exploiting Group-Sparsity
Jakob Möderl, Franz Pernkopf, Klaus Witrisal +1
In this paper, we present a variational inference algorithm that decomposes a signal into multiple groups of related spectral lines. The spectral lines in each group are associated…
Variational Message Passing-Based Respiratory Motion Estimation and Detection Using Radar Signals
Jakob Möderl, Erik Leitinger, Franz Pernkopf +1
We present a variational message passing (VMP) approach to detect the presence of a person based on their respiratory chest motion using multistatic ultra-wideband (UWB) radar. In…