Continuous-depth Models

Neural ordinary differential equations (Neural ODEs) are a class of machine learning models that represent the transformation of data through continuous dynamics defined by differential equations. Introduced in 2018, Neural ODEs generalize traditional discrete neural networks by modeling hidden layers as the solution to an ordinary differential equation parameterized by a neural network.