gpjax
https://github.com/jaxgaussianprocesses/gpjax
Python
Gaussian processes in JAX.
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- Issues
- Spec: didactic marimo notebook recreating arXiv:2608.04664 (soft-noncrossing Bayesian panel QR) with GPJax v1.0 + NumPyro
- `GaussianDistribution.kl_divergence` raises for `BlockDiag` and `Kronecker` covariances
- dev: Adopt the abstract/final pattern from Equinox
- Natural/Expectation variational families lack NGD machinery and can leave the PD cone
- State-space RTS smoother is covariance-form despite 'square-root' docstring
- Delete the dead `_gram` computation method (RFF computes features twice)
- OILMM `predict` defaults to a dense O(M N² P²) covariance
- Merge `_newton_girard` and `_newton_girard_matrices` (OAK/Sobol)
- Wire `bench-check` into `all-tests` poe sequence (post-bench-bootstrap)
- Hsgp
- Docs
- Python not yet supported