Example tutorial notebooks on the use of cd-dynamax

CD-LGGSM tutorial on how to sample from a continuous-discrete linear SDE model, filter observed data and fit model parameters to data using SGD. It also illustrates how to handle different data-streams, each with their own emission times.

Filtering tutorial on how to filter observed data of a continuous-discrete SDE model, based on different filtering algorithms.

Filtering-based likelihood tutorial on computing filtering-based likelihoods for continuous-discrete SDEs.

SGD-based model fitting tutorial on SGD-based fitting a continuous-discrete SDE model to data.

MCMC-based model fitting tutorial on MCMC-based fitting a continuous-discrete SDE model to data.

SGD-based Neural Network drift fitting tutorial on how to learn a continuous-discrete SDE drift function using Neural Networks, to fit model to observed data.

Differentiable Particle Filter for Poisson data tutorial on how to use a differentiable particle filter to fit a continuous-discrete SDE model (the Ornstein–Uhlenbeck process) with Poisson emissions.

Comparison of a Differentiable Particle Filter and Ensemble Kalman Filter a tracking example with non-Gaussian observations, where observations consist of a bearing estimate (that lives in the circle, $S^1$) and a power estimate (that lives in $\mathbb{R}$).