Neural ODE Tutorial

My lecture notes at Nordic Probabilistic AI School 2022. The lecture content is under this notebook (the notebook does not render on browser due to its size).

• Requires numpy, scipy, matplotlib, sklearn, Pillow, torch, torchdiffeq, torchvision.
• This folder contains trained models, datasets and visualizations. You should place etc folder insinde this repo.

The notebook contains the following sections:

1. Formal Descriptions of ODEs
2. Neural ODEs
3. Latent Bayesian Neural ODEs
4. ResNets are Discretized ODEs
5. Continuous-time Normalizing Flows
6. Related Studies