5 papers
Sparse Bayesian Learning for Label Efficiency in Cardiac Real-Time MRI
Felix Terhag, Philipp Knechtges, Achim Basermann +4
Cardiac real-time magnetic resonance imaging (MRI) is an emerging technology that images the heart at up to 50 frames per second, offering insight into the respiratory effects on t…
Uncertainty Quantification in Machine Learning Based Segmentation: A Post-Hoc Approach for Left Ventricle Volume Estimation in MRI
F. Terhag, P. Knechtges, A. Basermann +1
Recent studies have confirmed cardiovascular diseases remain responsible for highest death toll amongst non-communicable diseases. Accurate left ventricular (LV) volume estimation…
Unbiased Parameter Estimation for Bayesian Inverse Problems
Neil K. Chada, Ajay Jasra, Mohamed Maama +1
In this paper we consider the estimation of unknown parameters in Bayesian inverse problems. In most cases of practical interest, there are several barriers to performing such esti…
Parameter Estimation for Partially Observed McKean-Vlasov Diffusions
Ajay Jasra, Mohamed Maama, Raul Tempone
In this article we consider likelihood-based estimation of static parameters for a class of partially observed McKean-Vlasov (POMV) diffusion process with discrete-time observation…
Estimation of uncertainties in the density driven flow in fractured porous media using MLMC
Dmitry Logashenko, Alexander Litvinenko, Raul Tempone +1
We use the Multi Level Monte Carlo method to estimate uncertainties in a Henry-like salt water intrusion problem with a fracture. The flow is induced by the variation of the densit…