595 citations · 734 across the 14 of their papers we have counts for
10 papers · 1 filter
Strategies to Minimize Out-of-Distribution Effects in Data-Driven MRS Quantification
Julian P. Merkofer, Antonia Kaiser, Anouk Schrantee +2
This study systematically compared data-driven and model-based strategies for metabolite quantification in magnetic resonance spectroscopy (MRS), focusing on resilience to out-of-d…
SubspaceNet: Deep Learning-Aided Subspace Methods for DoA Estimation
Dor H. Shmuel, Julian P. Merkofer, Guy Revach +2
Direction of arrival (DoA) estimation is a fundamental task in array processing. A popular family of DoA estimation algorithms are subspace methods, which operate by dividing the m…
Latent-KalmanNet: Learned Kalman Filtering for Tracking from High-Dimensional Signals
Itay Buchnik, Damiano Steger, Guy Revach +3
The Kalman filter (KF) is a widely-used algorithm for tracking dynamic systems that are captured by state space (SS) models. The need to fully describe a SS model limits its applic…
Unsupervised Learned Kalman Filtering
Guy Revach, Nir Shlezinger, Timur Locher +3
In this paper we adapt KalmanNet, which is a recently pro-posed deep neural network (DNN)-aided system whose architecture follows the operation of the model-based Kalman filter (KF…
Uncertainty in Data-Driven Kalman Filtering for Partially Known State-Space Models
Itzik Klein, Guy Revach, Nir Shlezinger +3
Providing a metric of uncertainty alongside a state estimate is often crucial when tracking a dynamical system. Classic state estimators, such as the Kalman filter (KF), provide a…
RTSNet: Learning to Smooth in Partially Known State-Space Models (Preprint)
Guy Revach, Xiaoyong Ni, Nir Shlezinger +2
The smoothing task is core to many signal processing applications. A widely popular smoother is the Rauch-Tung-Striebel (RTS) algorithm, which achieves minimal mean-squared error r…
Deep Learning for Ultrasound Beamforming
Ruud JG van Sloun, Jong Chul Ye, Yonina C Eldar
Diagnostic imaging plays a critical role in healthcare, serving as a fundamental asset for timely diagnosis, disease staging and management as well as for treatment choice, plannin…
DA-MUSIC: Data-Driven DoA Estimation via Deep Augmented MUSIC Algorithm
Julian P. Merkofer, Guy Revach, Nir Shlezinger +2
Direction of arrival (DoA) estimation of multiple signals is pivotal in sensor array signal processing. A popular multi-signal DoA estimation method is the multiple signal classifi…
KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics
Guy Revach, Nir Shlezinger, Xiaoyong Ni +3
State estimation of dynamical systems in real-time is a fundamental task in signal processing. For systems that are well-represented by a fully known linear Gaussian state space (S…
Super-resolution Ultrasound Localization Microscopy through Deep Learning
Ruud J. G. van Sloun, Oren Solomon, Matthew Bruce +4
Ultrasound localization microscopy has enabled super-resolution vascular imaging through precise localization of individual ultrasound contrast agents (microbubbles) across numerou…