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Improving Interpretability and Regularisation in Deep Learning


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Type

Dataset

Change log

Authors

Ragni, Anton 
Karanasou, Penny 
Sim, Khe Chai 

Description

The provided .ctm and scoring .sys files correspond to the MPE systems of Table VI (Javanese) and Table X (BN) of this paper.

Version

Software / Usage instructions

HTK Toolkit, NIST SCLITE Scoring Package

Keywords

activation regularisation, interpretability, visualisation, neural network, deep learning

Publisher

Sponsorship
IARPA (4912046943)
EPSRC (via University of Edinburgh) (EP/I031022/1 ERI016379)
Relationships
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