Journal Club: Chen et al, 2018: Neural Ordinary Differential Equations

In the 2018 NeurIPS conference, 4,845 papers were submitted. The paper I’m reviewing here by Chen et al, 2018, titled Neural Ordinary Differential Equations, won best paper award. The paper discusses using continuous Ordinary Differential Equations (ODE) for Neural Networks (NN) as opposed to the sorts of discrete layers used in the standard Recurrent Neural Networks (RNN).

Continue reading “Journal Club: Chen et al, 2018: Neural Ordinary Differential Equations”