1 citations · 1 across the 1 of their papers we have counts for
4 papers
Dynamic Probabilistic Pruning: A general framework for hardware-constrained pruning at different granularities
Lizeth Gonzalez-Carabarin, Iris A. M. Huijben, Bastiaan S. Veeling +2
Unstructured neural network pruning algorithms have achieved impressive compression rates. However, the resulting - typically irregular - sparse matrices hamper efficient hardware…
Overfitting for Fun and Profit: Instance-Adaptive Data Compression
Ties van Rozendaal, Iris A. M. Huijben, Taco S. Cohen
Neural data compression has been shown to outperform classical methods in terms of performance, with results still improving rapidly. At a high level, neural compression is ba…
Learning Sampling and Model-Based Signal Recovery for Compressed Sensing MRI
Iris A. M. Huijben, Bastiaan S. Veeling, Ruud J. G. van Sloun
Compressed sensing (CS) MRI relies on adequate undersampling of the k-space to accelerate the acquisition without compromising image quality. Consequently, the design of optimal sa…
Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging
Iris A. M. Huijben, Bastiaan S. Veeling, Kees Janse +2
Limitations on bandwidth and power consumption impose strict bounds on data rates of diagnostic imaging systems. Consequently, the design of suitable (i.e. task- and data-aware) co…