Before revision:  In this paper, we propose a new class of interpretable neural network models that can achieve both high prediction accuracy and interpretability in regression problems with time series cross-sectional data. Our model can essentially be written as a simple function of a limited number of interpretable features .
After revision:  In this paper, we propose a new class of interpretable neural network models that can achieve both high prediction accuracy and interpretability . The model can be written as a simple function of a limited number of interpretable features .