We have recently developed an Adjoint based Neural ODE (ANODE) which computes unconditionally accurate gradients for Neural ODEs. This is very important as the approach presented in arxiv:1806.07366 is numerically unstable and may result in divergent training (in several cases we observed >20% accuracy degradation because of this)

Link to Pytorch code:

https://github.com/amirgholami/anode

​

Link to papers:

https://arxiv.org/pdf/1902.10298.pdf

https://arxiv.org/pdf/1906.04596.pdf

​

We hope this library would be helpful. Please let us know if you have any feedback and feel free to reach out if there was any questions