Bayesian polynomial neural networks and polynomial neural ordinary differential equations
Fig 9
For the Lotka Volterra Oscillator, we show the predictive performance of a Bayesian polynomial neural ODE trained using a) the Laplace Approximation, b) Markov Chain Monte Carlo, and c) Variational Inference. The solid red and blue dots indicate the training data, solid green lines indicate the true ODE model, dashed lines indicate the predictive mean model, and shaded regions indicate 95% and 99.75% credible intervals.