News for hackers. Stuff that matters.
Re:Neural Ordinary Differential Equations by byt143 on Thursday December 13, 2018 @10:21PM (#18678171)
How does this relate to previous work that's described NNets in the limit of infinite width as GPs?
Re:Neural Ordinary Differential Equations by duvenaud on Thursday December 13, 2018 @10:35PM (#18678251)
Ooo, great question. In both cases, we define a function using a sum over an infinite number of infinitesimal things.

In the GP case, those things are random and independent of each other, so the central limit theorem applies and we get a simple Gaussian.

In the ODE case, the infinitesimals are deterministic and depend on the previous ones in the sequence, so the final answer is deterministic and impossible to compute exactly in general.

You could also use a GP to model the dynamics of an ODE, and this was done recently: [https://arxiv.org/abs/1803.04303] although the drawback was that they couldn't train the model by backpropagation.