smolgp 0.0.1

Gaussian Process State Space Models in Python/JAX

smolgp
State Space Models for O(Linear/Log) Gaussian Processes

smolgp is a Python/JAX extension of the tinygp package that implements

1. A Kalman filter and RTS smoother as a StateSpaceSolver compatible with tinygp-like GP kernels.
2. An IntegratedStateSpaceSolver that can handle integrated (and possibly overlapping) measurements from mutliple instruments (see Rubenzahl and Hattori et al. in prep)
3. Parallelized versions of 1 (see Särkkä and García-Fernández 2020) and 2 (see Yaghoobi and Särkkä 2024 and its implementation) using jax.lax.associative_scan

TODO:

• benchmark plots from paper/showing full GP vs. QSM GP vs. SSM vs. parallel SSM
• doc/example useage
• tests

Possible additions

• define other kernels not in tinygp