Neural Ordinary Differential Equations
Senior author here, I'm happy to answer any questions.<p>We just released source code:
<a href="https://github.com/rtqichen/torchdiffeq" rel="nofollow">https://github.com/rtqichen/torchdiffeq</a> .
This includes PyTorch implementations of adaptive ODE solvers that can be differentiated through automatically.  So you can mix and match these ODE solvers with any other differentiable model component.<p>There's already been a bit of follow-up work, turning Continuous Normalizing Flows into a practical generative density model:
<a href="https://arxiv.org/abs/1810.01367" rel="nofollow">https://arxiv.org/abs/1810.01367</a><p>And now we're mainly working on 1) Regularizing ODE nets to be faster to solve and 2) getting the time-series model to scale up and extend it to stochastic differential equations.