  In recent years, there has been considerable innovation in the world of
predictive methodologies. This is evident by the relative domination of machine
learning approaches in various classification competitions. While these
algorithms have excelled at multivariate problems, they have remained dormant
in the realm of functional data analysis. We extend notable deep learning
methodologies to the domain of functional data for the purpose of
classification problems. We highlight the effectiveness of our method in a
number of classification applications such as classification of spectrographic
data. Moreover, we demonstrate the performance of our classifier through
simulation studies in which we compare our approach to the functional linear
model and other conventional classification methods.
