335 citations · 499 across the 11 of their papers we have counts for
4 papers · 1 filter
Improved Bayesian Compression
Marco Federici, Karen Ullrich, Max Welling
Compression of Neural Networks (NN) has become a highly studied topic in recent years. The main reason for this is the demand for industrial scale usage of NNs such as deploying th…
Optical Music Recognition with Convolutional Sequence-to-Sequence Models
Eelco van der Wel, Karen Ullrich
Optical Music Recognition (OMR) is an important technology within Music Information Retrieval. Deep learning models show promising results on OMR tasks, but symbol-level annotated…
Bayesian Compression for Deep Learning
Christos Louizos, Karen Ullrich, Max Welling
Compression and computational efficiency in deep learning have become a problem of great significance. In this work, we argue that the most principled and effective way to attack t…
Soft Weight-Sharing for Neural Network Compression
Karen Ullrich, Edward Meeds, Max Welling
The success of deep learning in numerous application domains created the de- sire to run and train them on mobile devices. This however, conflicts with their computationally, memor…