| Deep learning for classification and localization of COVID-19 markers in point-of-care lung ultrasound S Roy, W Menapace, S Oei, B Luijten, E Fini, C Saltori, I Huijben, ... IEEE transactions on medical imaging 39 (8), 2676-2687, 2020 | 449 | 2020 |
| Learning sub-sampling and signal recovery with applications in ultrasound imaging IAM Huijben, BS Veeling, K Janse, M Mischi, RJG van Sloun IEEE Transactions on Medical Imaging 39 (12), 3955-3966, 2020 | 44 | 2020 |
| Deep probabilistic subsampling for task-adaptive compressed sensing IAM Huijben, BS Veeling, RJG van Sloun International Conference on Learning Representations, 2020 | 29 | 2020 |
| Learning sampling and model-based signal recovery for compressed sensing MRI IAM Huijben, BS Veeling, RJG van Sloun ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 26 | 2020 |
| A review of the gumbel-max trick and its extensions for discrete stochasticity in machine learning IAM Huijben, W Kool, MB Paulus, RJG Van Sloun IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (2), 1353-1371, 2022 | 24 | 2022 |
| Learning task-based analog-to-digital conversion for MIMO receivers N Shlezinger, RJG Van Sloun, IAM Huijben, G Tsintsadze, YC Eldar ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 18 | 2020 |
| Overfitting for fun and profit: Instance-adaptive data compression T van Rozendaal, IAM Huijben, TS Cohen arXiv preprint arXiv:2101.08687, 2021 | 11 | 2021 |
| Active deep probabilistic subsampling H Van Gorp, I Huijben, BS Veeling, N Pezzotti, RJG Van Sloun International Conference on Machine Learning, 10509-10518, 2021 | 8 | 2021 |
| Certainty about uncertainty in sleep staging: a theoretical framework H van Gorp, IAM Huijben, P Fonseca, RJG van Sloun, S Overeem, ... Sleep 45 (8), zsac134, 2022 | 5 | 2022 |
| Dynamic probabilistic pruning: A general framework for hardware-constrained pruning at different granularities L Gonzalez-Carabarin, IAM Huijben, B Veeling, A Schmid, RJG van Sloun IEEE Transactions on Neural Networks and Learning Systems, 2022 | 5 | 2022 |
| Instance-adaptive image and video compression using machine learning systems TJ Van Rozendaal, IAM Huijben, TS Cohen US Patent App. 17/201,944, 2022 | 4 | 2022 |
| Representations of temporal sleep dynamics: Review and synthesis of the literature LWA Hermans, IAM Huijben, H van Gorp, TRM Leufkens, P Fonseca, ... Sleep Medicine Reviews, 101611, 2022 | 4 | 2022 |
| Interpretation and further development of the hypnodensity representation of sleep structure IAM Huijben, LWA Hermans, AC Rossi, S Overeem, MM van Gilst, ... Physiological Measurement, 2022 | 1 | 2022 |
| SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series IAM Huijben, AA Nijdam, S Overeem, MM van Gilst, RJG van Sloun arXiv preprint arXiv:2205.15875, 2022 | 1 | 2022 |
| Contrastive Predictive Coding for Anomaly Detection of Fetal Health from the Cardiotocogram IR de Vries, IAM Huijben, RD Kok, RJG van Sloun, R Vullings ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 1 | 2022 |
| SOM-CPC: a new clustering method for sleep recordings to facilitate pattern recognition I Huijben, R van Sloun, S Overeem, M van Gilst JOURNAL OF SLEEP RESEARCH 31, 2022 | | 2022 |
| Self-Organizing Maps for Contrastive Embeddings of Sleep Recordings IAM Huijben, AA Nijdam, LWA Hermans, S Overeem, MM Van Gilst, ... 2022 44th Annual International Conference of the IEEE Engineering in …, 2022 | | 2022 |
| Predicting co-existence of sources through self-supervised Contrastive Predictive Coding to reveal underlying structures during sleep I Huijben, L Hermans, M van Gilst, R van Sloun, S Overeem and Signal Processing in the Benelux, May 20-21, TU Eindhoven, 141, 0 | | |
| Dynamic Probabilistic Pruning: Training sparse networks based on stochastic and dynamic masking LG Carabarin, IAM Huijben, BS Veeling, A Schmid, R Van Sloun | | |
