Iris A. M. Huijben

Orcid: 0000-0002-2629-3898

According to our database1, Iris A. M. Huijben authored at least 15 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Dynamic Probabilistic Pruning: A General Framework for Hardware-Constrained Pruning at Different Granularities.
IEEE Trans. Neural Networks Learn. Syst., January, 2024

Learning Structured Compressed Sensing with Automatic Resource Allocation.
CoRR, 2024

Residual Quantization with Implicit Neural Codebooks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series.
Proceedings of the International Conference on Machine Learning, 2023

2022
Contrastive Predictive Coding for Anomaly Detection of Fetal Health from the Cardiotocogram.
Proceedings of the IEEE International Conference on Acoustics, 2022

Self-Organizing Maps for Contrastive Embeddings of Sleep Recordings.
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.
CoRR, 2021

Active Deep Probabilistic Subsampling.
Proceedings of the 38th International Conference on Machine Learning, 2021

Overfitting for Fun and Profit: Instance-Adaptive Data Compression.
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.
IEEE Trans. Medical Imaging, 2020

Learning Sub-Sampling and Signal Recovery With Applications in Ultrasound Imaging.
IEEE Trans. Medical Imaging, 2020

Deep probabilistic subsampling for task-adaptive compressed sensing.
Proceedings of the 8th International Conference on Learning Representations, 2020

Learning Task-Based Analog-to-Digital Conversion for MIMO Receivers.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Learning Sampling and Model-Based Signal Recovery for Compressed Sensing MRI.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020


  Loading...