Iris AM Huijben
Iris AM Huijben
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Zitiert von
Zitiert von
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
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
Deep probabilistic subsampling for task-adaptive compressed sensing
IAM Huijben, BS Veeling, RJG van Sloun
International Conference on Learning Representations, 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
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
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
Overfitting for fun and profit: Instance-adaptive data compression
T van Rozendaal, IAM Huijben, TS Cohen
arXiv preprint arXiv:2101.08687, 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
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
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
Instance-adaptive image and video compression using machine learning systems
TJ Van Rozendaal, IAM Huijben, TS Cohen
US Patent App. 17/201,944, 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
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
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
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
SOM-CPC: a new clustering method for sleep recordings to facilitate pattern recognition
I Huijben, R van Sloun, S Overeem, M van Gilst
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
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
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