Graph Neural Ordinary Differential Equations

Often, closed -- form analytic formulations are not available and forecasting or decision making tasks have to rely on noisy, irregularly sampled observations. This class of systems offers a crystal clear example of inductive relational biases. Introducing inductive biases in statistics or machine learning is a well known approach to improving sample efficiency and generalization performance. From the choice of objective function, to the design of ad -- hoc deep learning architectures suited to the specific problem at hand, biases are common and effective. Relational inductive biases [1] represent a special class of biases, concerned with relationship between entities.