Reviews: ODE2VAE: Deep generative second order ODEs with Bayesian neural networks

Summary: The paper looks at the problem of modelling sequential data, specifically image data. It proposes to combine a (beta-)VAE model with a Neural ODE. The VAE encodes the input image to a location and velocity, the Neural ODE computes the dynamics over time, the VAE then decodes using the location parameters. To model the velocity, the authors extend the Neural ODE to be second order. The paper contains extensive introduction to the method, including ODE, VI, beta-VAE, generative models, ODE flow.