Ultrasonic circular array sensing for human arm motion classification. - Ruud van Sloun; Ashish Pandharipande; David Caicedo; Sriram Srinivasan 003; Piet Sommen (ICCE-Berlin, 2014)

Compressed Sensing for Ultrasound Computed Tomography. - Ruud van Sloun; Ashish Pandharipande; Massimo Mischi; Libertario Demi (IEEE Trans. Biomed. Eng., 2015)

Ultrasound-contrast-agent dispersion and velocity imaging for prostate cancer localization. - Ruud van Sloun; Libertario Demi; Arnoud Postema; Jean J. M. C. H. de la Rosette; Hessel Wijkstra; Massimo Mischi (Medical Image Anal., 2017)

Entropy of Ultrasound-Contrast-Agent Velocity Fields for Angiogenesis Imaging in Prostate Cancer. - Ruud J. G. van Sloun; Libertario Demi; Arnoud W. Postema; Jean J. M. C. H. de la Rosette; Hessel Wijkstra; Massimo Mischi (IEEE Trans. Medical Imaging, 2017)

Dynamic velocity vector and relative pressure estimation in the left ventricle with dynamic contrast-enhanced ultrasound of low frame rates. - Peiran Chen; Ruud J. G. van Sloun; Simona Turco; Hessel Wijkstra; Patrick Houthuizen; Massimo Mischi (MeMeA, 2018)

A fixed-distance plane wave method for estimating the ultrasound coefficient of nonlinearity. - Anastasiia Panfilova; Ruud J. G. van Sloun; Rogier R. Wildeboer; Hessel Wijkstra; Massimo Mischi (Proc. Meet. Acoust., 2018)

Convective-Dispersion Modeling in 3D Contrast-Ultrasound Imaging for the Localization of Prostate Cancer. - Rogier R. Wildeboer; Ruud J. G. van Sloun; Stefan G. Schalk; Christophe K. Mannaerts; J. C. Van Der Linden; Pintong Huang; Hessel Wijkstra; Massimo Mischi (IEEE Trans. Medical Imaging, 2018)

Deep Convolutional Robust PCA with Application to Ultrasound Imaging. - Regev Cohen; Yi Zhang 117; Oren Solomon; Daniel Toberman; Liran Taieb; Ruud J. G. van Sloun; Yonina C. Eldar (ICASSP, 2019)

Deep Learning for Fast Adaptive Beamforming. - Ben Luijten; Regev Cohen; Frederik J. de Bruijn; Harold A. W. Schmeitz; Massimo Mischi; Yonina C. Eldar; Ruud J. G. van Sloun (ICASSP, 2019)

Deep Learning for Super-resolution Vascular Ultrasound Imaging. - Ruud J. G. van Sloun; Oren Solomon; Matthew Bruce; Zin Z. Khaing; Yonina C. Eldar; Massimo Mischi (ICASSP, 2019)

Super-resolution Using Flow Estimation in Contrast Enhanced Ultrasound Imaging. - Oren Solomon; Ruud J. G. van Sloun; Massimo Mischi; Yonina C. Eldar (ICASSP, 2019)

B-line Detection and Localization by Means of Deep Learning: Preliminary In-vitro Results. - Ruud J. G. van Sloun; Libertario Demi (ICIAR (1), 2019)

Deep Learning Biopsy Marking of Early Neoplasia in Barrett's Esophagus by Combining WLE and BLI Modalities. - Joost van der Putten; Rogier R. Wildeboer; Jeroen de Groof; Ruud van Sloun; Maarten R. Struyvenberg; Fons van der Sommen; Svitlana Zinger; Wouter L. Curvers; Erik J. Schoon; Jacques J. Bergman; Peter H. N. de With (ISBI, 2019)

Synthetic Elastography using B-mode Ultrasound through a Deep Fully-Convolutional Neural Network. - Rogier R. Wildeboer; Ruud J. G. van Sloun; Christophe K. Mannaerts; Georg Salomon; Hessel Wijkstra; Massimo Mischi (CoRR, 2019)

Deep Convolutional Long Short-Term Memory Network for Fetal Heart Rate Extraction. - Eleni Fotiadou; Mengzhu Xu; Bart van Erp; Ruud J. G. van Sloun; Rik Vullings (EMBC, 2020)

Learning Sampling and Model-Based Signal Recovery for Compressed Sensing MRI. - Iris A. M. Huijben; Bastiaan S. Veeling; Ruud J. G. van Sloun (ICASSP, 2020)

Learning Task-Based Analog-to-Digital Conversion for MIMO Receivers. - Nir Shlezinger; Ruud J. G. van Sloun; Iris A. M. Huijben; Georgee Tsintsadze; Yonina C. Eldar (ICASSP, 2020)

ProxSGD: Training Structured Neural Networks under Regularization and Constraints. - Yang Yang 033; Yaxiong Yuan; Avraam Chatzimichailidis; Ruud J. G. van Sloun; Lei Lei 001; Symeon Chatzinotas (ICLR, 2020)

Deep probabilistic subsampling for task-adaptive compressed sensing. - Iris A. M. Huijben; Bastiaan S. Veeling; Ruud J. G. van Sloun (ICLR, 2020)

Artificial intelligence in multiparametric prostate cancer imaging with focus on deep-learning methods. - Rogier R. Wildeboer; Ruud J. G. van Sloun; Hessel Wijkstra; Massimo Mischi (Comput. Methods Programs Biomed., 2020)

Deep Learning in Ultrasound Imaging. - Ruud J. G. van Sloun; Regev Cohen; Yonina C. Eldar (Proc. IEEE, 2020)

Localizing B-Lines in Lung Ultrasonography by Weakly Supervised Deep Learning, In-Vivo Results. - Ruud J. G. van Sloun; Libertario Demi (IEEE J. Biomed. Health Informatics, 2020)

Learning Sub-Sampling and Signal Recovery With Applications in Ultrasound Imaging. - Iris A. M. Huijben; Bastiaan S. Veeling; Kees Janse; Massimo Mischi; Ruud J. G. van Sloun (IEEE Trans. Medical Imaging, 2020)

Adaptive Ultrasound Beamforming Using Deep Learning. - Ben Luijten; Regev Cohen; Frederik J. de Bruijn; Harold A. W. Schmeitz; Massimo Mischi; Yonina C. Eldar; Ruud J. G. van Sloun (IEEE Trans. Medical Imaging, 2020)

Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound. - Subhankar Roy; Willi Menapace; Sebastiaan Oei; Ben Luijten; Enrico Fini; Cristiano Saltori; Iris A. M. Huijben; Nishith Chennakeshava; Federico Mento; Alessandro Sentelli; Emanuele Peschiera; Riccardo Trevisan; et al. (IEEE Trans. Medical Imaging, 2020)

Deep Unfolded Robust PCA With Application to Clutter Suppression in Ultrasound. - Oren Solomon; Regev Cohen; Yi Zhang 117; Yi Yang 045; Qiong He; Jianwen Luo 001; Ruud J. G. van Sloun; Yonina C. Eldar (IEEE Trans. Medical Imaging, 2020)

Hardware-oriented pruning and quantization of Deep Learning models to detect life-threatening arrhythmias. - Lizeth Gonzalez-Carabarin; Alexandre Schmid; Ruud J. G. van Sloun (BioCAS, 2021)

Automated Gain Control Through Deep Reinforcement Learning for Downstream Radar Object Detection. - Tristan S. W. Stevens; R. Firat Tigrek; Eric S. Tammam; Ruud J. G. van Sloun (EUSIPCO, 2021)

Kalmannet: Data-Driven Kalman Filtering. - Guy Revach; Nir Shlezinger; Ruud J. G. van Sloun; Yonina C. Eldar (ICASSP, 2021)

Active Deep Probabilistic Subsampling. - Hans Van Gorp; Iris A. M. Huijben; Bastiaan S. Veeling; Nicola Pezzotti; Ruud J. G. van Sloun (ICML, 2021)

Joint Performance Optimization of Monostatic and Bistatic SAR Configurations. - Nehir Berk Onat; Ozan Dogan; Mario Azcueta; Ruud van Sloun (IGARSS, 2021)

Improving Aleatoric Uncertainty Quantification in Multi-annotated Medical Image Segmentation with Normalizing Flows. - M. M. Amaan Valiuddin; Christiaan G. A. Viviers; Ruud J. G. van Sloun; Peter H. N. de With; Fons van der Sommen (UNSURE/PIPPI@MICCAI, 2021)

Blood flow patterns estimation in the left ventricle with low-rate 2D and 3D dynamic contrast-enhanced ultrasound. - Peiran Chen; Ruud J. G. van Sloun; Simona Turco; Hessel Wijkstra; Domenico Filomena; Luciano Agati; Patrick Houthuizen; Massimo Mischi (Comput. Methods Programs Biomed., 2021)

Improving Aleatoric Uncertainty Quantification in Multi-Annotated Medical ImageSegmentation with Normalizing Flows. - M. M. Amaan Valiuddin; Christiaan G. A. Viviers; Ruud J. G. van Sloun; Peter H. N. de With; Fons van der Sommen (CoRR, 2021)

Deep Learning for Ultrasound Beamforming. - Ruud J. G. van Sloun; Jong Chul Ye; Yonina C. Eldar (CoRR, 2021)

A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning. - Iris A. M. Huijben; Wouter Kool 002; Max B. Paulus; Ruud J. G. van Sloun (CoRR, 2021)

Ultrasound Speckle Suppression and Denoising using MRI-derived Normalizing Flow Priors. - Vincent van de Schaft; Ruud J. G. van Sloun (CoRR, 2021)

Super-Resolution Ultrasound Localization Microscopy Through Deep Learning. - Ruud J. G. van Sloun; Oren Solomon; Matthew Bruce; Zin Z. Khaing; Hessel Wijkstra; Yonina C. Eldar; Massimo Mischi (IEEE Trans. Medical Imaging, 2021)

Self-Organizing Maps for Contrastive Embeddings of Sleep Recordings. - Iris A. M. Huijben; Arthur A. Nijdam; Lieke W. A. Hermans; Sebastiaan Overeem; Merel M. van Gilst; Ruud J. G. van Sloun (EMBC, 2022)

A U - Net Deep Learning Model for Infant Heart Rate Estimation from Ballistography*. - Wendy Prins; Elena Stamatelou; Kiran Dellimore; Alice Likumbo; Emmanuel Kafulafula; Josephine Langton; Jenala Njirammadzi; Joyce Mwenisungo; Tushapo Msukwa; Job Calis; Ruud van Sloun; Bart Bierling (EMBC, 2022)

Unsupervised Learned Kalman Filtering. - Guy Revach; Nir Shlezinger; Timur Locher; Xiaoyong Ni; Ruud J. G. van Sloun; Yonina C. Eldar (EUSIPCO, 2022)

Deep Proximal Unfolding For Image Recovery from Under-Sampled Channel Data in Intravascular Ultrasound. - Nishith Chennakeshava; Tristan S. W. Stevens; Frederik J. de Bruijn; Andrew Hancock; Martin Pekar; Yonina C. Eldar; Massimo Mischi; Ruud J. G. van Sloun (ICASSP, 2022)

Unfolding Model-Based Beamforming for High Quality Ultrasound Imaging. - Christopher Khan; Ruud J. G. van Sloun; Brett C. Byram (ICASSP, 2022)

Uncertainty in Data-Driven Kalman Filtering for Partially Known State-Space Models. - Itzik Klein; Guy Revach; Nir Shlezinger; Jonas E. Mehr; Ruud J. G. van Sloun; Yonina C. Eldar (ICASSP, 2022)

Deep Augmented Music Algorithm for Data-Driven Doa Estimation. - Julian P. Merkofer; Guy Revach; Nir Shlezinger; Ruud J. G. van Sloun (ICASSP, 2022)

RTSNet: Deep Learning Aided Kalman Smoothing. - Xiaoyong Ni; Guy Revach; Nir Shlezinger; Ruud J. G. van Sloun; Yonina C. Eldar (ICASSP, 2022)

Accelerated Intravascular Ultrasound Imaging using Deep Reinforcement Learning. - Tristan S. W. Stevens; Nishith Chennakeshava; Frederik J. de Bruijn; Martin Pekar; Ruud J. G. van Sloun (ICASSP, 2022)

Contrastive Predictive Coding for Anomaly Detection of Fetal Health from the Cardiotocogram. - Bert de Vries; Iris A. M. Huijben; René D. Kok; Ruud J. G. van Sloun; Rik Vullings (ICASSP, 2022)

Image Denoising with Deep Unfolding And Normalizing Flows. - Xinyi Wei; Hans Van Gorp; Lizeth Gonzalez-Carabarin; Daniel Freedman; Yonina C. Eldar; Ruud J. G. van Sloun (ICASSP, 2022)

Structured and tiled-based pruning of Deep Learning models targeting FPGA implementations. - Lizeth Gonzalez-Carabarin; Alexandre Schmid; Ruud J. G. van Sloun (ISCAS, 2022)

Efficient Out-of-Distribution Detection of Melanoma with Wavelet-Based Normalizing Flows. - M. M. Amaan Valiuddin; Christiaan G. A. Viviers; Ruud J. G. van Sloun; Peter H. N. de With; Fons van der Sommen (CaPTion@MICCAI, 2022)

Unsupervised domain adaptation method for segmenting cross-sectional CCA images. - Luuk van Knippenberg; Ruud J. G. van Sloun; Massimo Mischi; Joerik de Ruijter; Richard G. P. Lopata; R. Arthur Bouwman (Comput. Methods Programs Biomed., 2022)

Ultrasound Signal Processing: From Models to Deep Learning. - Ben Luijten; Nishith Chennakeshava; Yonina C. Eldar; Massimo Mischi; Ruud J. G. van Sloun (CoRR, 2022)

KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics. - Guy Revach; Nir Shlezinger; Xiaoyong Ni; Adrià López Escoriza; Ruud J. G. van Sloun; Yonina C. Eldar (IEEE Trans. Signal Process., 2022)

Deep Task-Based Analog-to-Digital Conversion. - Nir Shlezinger; Ariel Amar; Ben Luijten; Ruud J. G. van Sloun; Yonina C. Eldar (IEEE Trans. Signal Process., 2022)

Deep Unfolding With Normalizing Flow Priors for Inverse Problems. - Xinyi Wei; Hans Van Gorp; Lizeth Gonzalez-Carabarin; Daniel Freedman; Yonina C. Eldar; Ruud J. G. van Sloun (IEEE Trans. Signal Process., 2022)

Learned Kalman Filtering in Latent Space with High-Dimensional Data. - Itay Buchnik; Damiano Steger; Guy Revach; Ruud J. G. van Sloun; Tirza Routtenberg; Nir Shlezinger (ICASSP, 2023)

Active Subsampling Using Deep Generative Models by Maximizing Expected Information Gain. - Koen C. E. van de Camp; Hamdi Joudeh; Duarte J. Antunes; Ruud J. G. van Sloun (ICASSP, 2023)

Aleatoric Uncertainty Estimation of Overnight Sleep Statistics Through Posterior Sampling Using Conditional Normalizing Flows. - Hans Van Gorp; Merel M. van Gilst; Pedro Fonseca 002; Sebastiaan Overeem; Ruud J. G. van Sloun (ICASSP, 2023)

Hierarchical Filtering With Online Learned Priors for ECG Denoising. - Timur Locher; Guy Revach; Nir Shlezinger; Ruud J. G. van Sloun; Rik Vullings (ICASSP, 2023)

Neural Maximum-a-Posteriori Beamforming for Ultrasound Imaging. - Ben Luijten; Boudewine W. Ossenkoppele; Nico de Jong; Martin D. Verweij; Yonina C. Eldar; Massimo Mischi; Ruud J. G. van Sloun (ICASSP, 2023)

Signal Reconstruction for FMCW Radar Interference Mitigation Using Deep Unfolding. - Jeroen Overdevest; A. G. C. Koppelaar; M. J. G. Bekooij; J. Youn; Ruud J. G. van Sloun (ICASSP, 2023)

Deep Root Music Algorithm for Data-Driven Doa Estimation. - Dor Haim Shmuel; Julian P. Merkofer; Guy Revach; Ruud J. G. van Sloun; Nir Shlezinger (ICASSP, 2023)

SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series. - Iris A. M. Huijben; Arthur Andreas Nijdam; Sebastiaan Overeem; Merel M. van Gilst; Ruud van Sloun (ICML, 2023)

Removing Structured Noise with Diffusion Models. - Tristan S. W. Stevens; Jean-Luc Robert; Faik C. Meral; Jason Yu; Jun Seob Shin; Ruud J. G. van Sloun (CoRR, 2023)

A Deep Learning Approach Utilizing Covariance Matrix Analysis for the ISBI Edited MRS Reconstruction Challenge. - Julian P. Merkofer; Dennis M. J. van de Sande; Sina Amirrajab; Gerhard S. Drenthen; Mitko Veta; Jacobus F. A. Jansen; Marcel Breeuwer; Ruud J. G. van Sloun (CoRR, 2023)

A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning. - Iris A. M. Huijben; Wouter Kool 001; Max B. Paulus; Ruud J. G. van Sloun (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

RTSNet: Learning to Smooth in Partially Known State-Space Models. - Guy Revach; Xiaoyong Ni; Nir Shlezinger; Ruud J. G. van Sloun; Yonina C. Eldar (IEEE Trans. Signal Process., 2023)

A deep-learning approach to assess respiratory effort with a chest-worn accelerometer during sleep. - Fons Schipper; Ruud J. G. van Sloun; Angela Grassi; Sebastiaan Overeem; Pedro Fonseca 002 (Biomed. Signal Process. Control., 2023)

Modeling the Impact of Inter-Rater Disagreement on Sleep Statistics Using Deep Generative Learning. - Hans Van Gorp; Merel M. van Gilst; Pedro Fonseca 002; Sebastiaan Overeem; Ruud J. G. van Sloun (IEEE J. Biomed. Health Informatics, 2023)

Automatic deep learning-based pleural effusion segmentation in lung ultrasound images. - Damjan Vukovic; Andrew Wang; Maria Antico; Marian Steffens; Igor Ruvinov; Ruud J. G. van Sloun; David Canty; Alistair Royse; Colin Royse; Kavi Haji; Jason Dowling; Girija Chetty; et al. (BMC Medical Informatics Decis. Mak., 2023)

Attention on Sleep Stage Specific Characteristics. - Iris A. M. Huijben; Sebastiaan Overeem; Merel M. van Gilst; Ruud J. G. van Sloun (EMBC, 2024)

Model-Based Diffusion for Mitigating Automotive Radar Interference. - Jeroen Overdevest; Xinyi Wei; Hans Van Gorp; Ruud J. G. van Sloun (ICASSP Workshops, 2024)

Retaining Informative Latent Variables in Probabilistic Segmentation. - M. M. Amaan Valiuddin; Christiaan G. A. Viviers; Ruud van Sloun; Peter H. N. de With; Fons van der Sommen (ICASSP, 2024)

Residual Quantization with Implicit Neural Codebooks. - Iris A. M. Huijben; Matthijs Douze; Matthew J. Muckley; Ruud van Sloun; Jakob Verbeek (ICML, 2024)

Exploring the trade-off between deep-learning and explainable models for brain-machine interfaces. - Luis Cubillos; Guy Revach; Matthew Mender; Joseph T. Costello; Hisham Temmar; Aren Hite; Diksha Anoop Kumar Zutshi; Dylan Wallace; Xiaoyong Ni; Madison Kelberman; Matt S. Willsey; Ruud van Sloun; et al. (NeurIPS, 2024)

Anomalous Change Point Detection Using Probabilistic Predictive Coding. - Roelof G. Hup; Julian P. Merkofer; Alex A. Bhogal; Ruud J. G. van Sloun; Reinder Haakma; Rik Vullings (CoRR, 2024)

A generative foundation model for five-class sleep staging with arbitrary sensor input. - Hans Van Gorp; Merel M. van Gilst; Pedro Fonseca 002; Fokke B. van Meulen; Johannes P. van Dijk; Sebastiaan Overeem; Ruud J. G. van Sloun (CoRR, 2024)

Active Inference for Closed-loop transmit beamsteering in Fetal Doppler Ultrasound. - Beatrice Federici; Ruud J. G. van Sloun; Massimo Mischi (CoRR, 2024)

Active inference and deep generative modeling for cognitive ultrasound. - Ruud J. G. van Sloun (CoRR, 2024)

A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation. - M. M. Amaan Valiuddin; Ruud J. G. van Sloun; Christiaan G. A. Viviers; Peter H. N. de With; Fons van der Sommen (CoRR, 2024)

Latent-KalmanNet: Learned Kalman Filtering for Tracking From High-Dimensional Signals. - Itay Buchnik; Guy Revach; Damiano Steger; Ruud J. G. van Sloun; Tirza Routtenberg; Nir Shlezinger (IEEE Trans. Signal Process., 2024)

HKF: Hierarchical Kalman Filtering With Online Learned Evolution Priors for Adaptive ECG Denoising. - Guy Revach; Timur Locher; Nir Shlezinger; Ruud J. G. van Sloun; Rik Vullings (IEEE Trans. Signal Process., 2024)

DA-MUSIC: Data-Driven DoA Estimation via Deep Augmented MUSIC Algorithm. - Julian P. Merkofer; Guy Revach; Nir Shlezinger; Tirza Routtenberg; Ruud J. G. van Sloun (IEEE Trans. Veh. Technol., 2024)

Dynamic Probabilistic Pruning: A General Framework for Hardware-Constrained Pruning at Different Granularities. - Lizeth Gonzalez-Carabarin; Iris A. M. Huijben; Bas Veeling; Alexandre Schmid; Ruud J. G. van Sloun (IEEE Trans. Neural Networks Learn. Syst., 2024)

The Transform-and-Perform Framework: Explainable Deep Learning Beyond Classification. - Vidya Prasad; Ruud J. G. van Sloun; Stef van den Elzen; Anna Vilanova; Nicola Pezzotti (IEEE Trans. Vis. Comput. Graph., 2024)

ULTRA-SR Challenge: Assessment of Ultrasound Localization and TRacking Algorithms for Super-Resolution Imaging. - Marcelo Lerendegui; Kai Riemer; Georgios Papageorgiou 001; Bingxue Wang; Lachlan Arthur; Arthur Chavignon; Tao Zhang; Olivier Couture; Pingtong Huang; Md Ashikuzzaman; Stefanie Dencks; Christopher Dunsby; et al. (IEEE Trans. Medical Imaging, 2024)

ProactiV: Studying Deep Learning Model Behavior Under Input Transformations. - Vidya Prasad; Ruud J. G. van Sloun; Anna Vilanova; Nicola Pezzotti (IEEE Trans. Vis. Comput. Graph., 2024)

Overnight Sleep Staging Using Chest-Worn Accelerometry. - Fons Schipper; Angela Grassi; Marco Ross; Andreas Cerny; Peter Anderer; Lieke W. A. Hermans; Fokke van Meulen; Mickey Leentjens; Emily Schoustra; Pien Bosschieter; Ruud J. G. van Sloun; Sebastiaan Overeem; et al. (Sensors, 2024)

Dehazing Ultrasound Using Diffusion Models. - Tristan S. W. Stevens; Faik C. Meral; Jason Yu; Iason Zacharias Apostolakis; Jean-Luc Robert; Ruud J. G. van Sloun (IEEE Trans. Medical Imaging, 2024)

Deep Learning for Modulo Sampling of FRI Signals. - Sem Koenen; Vincent van de Schaft; Ruud J. G. van Sloun (ICASSP, 2025)

Deep Variational Sequential Monte Carlo for High-Dimensional Observations. - Wessel L. van Nierop; Nir Shlezinger; Ruud J. G. van Sloun (ICASSP, 2025)

Deep Sylvester Posterior Inference for Adaptive Compressed Sensing in Ultrasound Imaging. - Simon W. Penninga; Hans Van Gorp; Ruud J. G. van Sloun (ICASSP, 2025)

Sequential Posterior Sampling with Diffusion Models. - Tristan S. W. Stevens; Oisín Nolan; Jean-Luc Robert; Ruud J. G. van Sloun (ICASSP, 2025)

Learning Structured Compressed Sensing with Automatic Resource Allocation. - Han Wang 052; Eduardo Pérez; Iris A. M. Huijben; Hans Van Gorp; Ruud van Sloun; Florian Römer (ICASSP, 2025)

Deep Unfolding Using Score-based Generative Networks for Automotive Radar Interference Mitigation. - Xinyi Wei; Jihwan Youn; Jeroen Overdevest; Jun Li 091; Satish Ravindran; Ruud J. G. van Sloun (ICASSP, 2025)

Adaptive multilevel thresholding for SVD-based clutter filtering in ultrafast transthoracic coronary flow imaging. - Yizhou Huang; Ruud van Sloun; Massimo Mischi (Comput. Methods Programs Biomed., 2025)

Active Diffusion Subsampling. - Oisín Nolan; Tristan S. W. Stevens; Wessel L. van Nierop; Ruud van Sloun (Trans. Mach. Learn. Res., 2025)

Removing Structured Noise using Diffusion Models. - Tristan S. W. Stevens; Hans Van Gorp; Faik C. Meral; Jun Seob Shin; Jason Yu; Jean-Luc Robert; Ruud van Sloun (Trans. Mach. Learn. Res., 2025)

Investigating and Improving Latent Density Segmentation Models for Aleatoric Uncertainty Quantification in Medical Imaging. - M. M. Amaan Valiuddin; Christiaan G. A. Viviers; Ruud J. G. van Sloun; Peter H. N. de With; Fons van der Sommen (IEEE Trans. Medical Imaging, 2025)

SubspaceNet: Deep Learning-Aided Subspace Methods for DoA Estimation. - Dor Haim Shmuel; Julian P. Merkofer; Guy Revach; Ruud J. G. van Sloun; Nir Shlezinger (IEEE Trans. Veh. Technol., 2025)

Physics-Informed Sylvester Normalizing Flows for Bayesian Inference in Magnetic Resonance Spectroscopy. - Julian P. Merkofer; Dennis M. J. van de Sande; Alex A. Bhogal; Ruud J. G. van Sloun (CoRR, 2025)

High Volume Rate 3D Ultrasound Reconstruction with Diffusion Models. - Tristan S. W. Stevens; Oisín Nolan; Oudom Somphone; Jean-Luc Robert; Ruud J. G. van Sloun (CoRR, 2025)

Dynamic Estimation Loss Control in Variational Quantum Sensing via Online Conformal Inference. - Ivana Nikoloska; Hamdi Joudeh; Ruud van Sloun; Osvaldo Simeone (CoRR, 2025)

Conditional Contrastive Predictive Coding for Assessment of Fetal Health From the Cardiotocogram. - Ivar R. de Vries; Raoul Melaet; Iris A. M. Huijben; Judith O. E. H. Van Laar; René D. Kok; S. Guid Oei; Ruud J. G. van Sloun; Rik Vullings (IEEE J. Biomed. Health Informatics, 2025)

Adaptive Bayesian Single-Shot Quantum Sensing. - Ivana Nikoloska; Ruud van Sloun; Osvaldo Simeone (CoRR, 2025)