Secondary vertex reconstruction is a key intermediate step in building powerful jet classifiers. We use a neural network to perform vertex finding inside jets in order to improve classification performance. This can be thought of as a supervised attention mechanism - directing the classifier towards the relevant information inside the jet. We show supervised attention outperforms an identical network with standard unsupervised attention.
|Academic Rank||PhD student|