Much of the data we encounter in everyday life is functional in nature. Examples include weather data, outputs from computer simulations, and measurements from sensor arrays. To utilize this data in deep learning, it’s often transformed into a different domain or summarized using statistics. Such transformations introduce an arbitrary discretization, even though it might be more straightforward to use the data in its original form. Recent studies suggest defining functional layers in neural networks to naturally incorporate functional data. This series compiles papers that address functional data within the context of deep learning and methods to integrate such data into neural networks.