Iris A. M. Huijben

According to our database, Iris A. M. Huijben authored at least 14 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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., January, 2024

Residual Quantization with Implicit Neural Codebooks.

Iris A. M. Huijben, Matthijs Douze, Matthew J. Muckley, Ruud van Sloun, Jakob Verbeek

CoRR, 2024

2023

A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning.

Iris A. M. Huijben, Wouter Kool, Max B. Paulus, Ruud J. G. van Sloun

IEEE Trans. Pattern Anal. Mach. Intell., 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

Proceedings of the International Conference on Machine Learning, 2023

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

Proceedings of the IEEE International Conference on Acoustics, 2022

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

Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

2021

A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning.

Iris A. M. Huijben, Wouter Kool, Max B. Paulus, Ruud J. G. van Sloun

CoRR, 2021

Active Deep Probabilistic Subsampling.

Hans Van Gorp, Iris A. M. Huijben, Bastiaan S. Veeling, Nicola Pezzotti, Ruud J. G. van Sloun

Proceedings of the 38th International Conference on Machine Learning, 2021

Overfitting for Fun and Profit: Instance-Adaptive Data Compression.

Ties van Rozendaal, Iris A. M. Huijben, Taco Cohen

Proceedings of the 9th International Conference on Learning Representations, 2021

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, Giovanni Maschietto, Elena Torri, Riccardo Inchingolo, Andrea Smargiassi, Gino Soldati, Paolo Rota, Andrea Passerini, Ruud J. G. van Sloun, Elisa Ricci, Libertario Demi

IEEE Trans. Medical Imaging, 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

Deep probabilistic subsampling for task-adaptive compressed sensing.

Iris A. M. Huijben, Bastiaan S. Veeling, Ruud J. G. van Sloun

Proceedings of the 8th International Conference on Learning Representations, 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

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Learning Sampling and Model-Based Signal Recovery for Compressed Sensing MRI.

Iris A. M. Huijben, Bastiaan S. Veeling, Ruud J. G. van Sloun

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020