gpjax
https://github.com/jaxgaussianprocesses/gpjax
Python
Gaussian processes in JAX.
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- Issues
- feat(kernels): nonstationary (VaryingAmplitude, Gibbs) and space–time (Gneiting) kernels
- feat(metrics): CRPS, PIT and interval coverage in gpjax.metrics
- feat(likelihoods): GEV likelihood and return levels, with an Ahr/Erft 2021 example
- feat: Vecchia approximation for large spatial data (design document first)
- feat(kernels): nonstationary kernels for climate data (amplitude, Gibbs/Paciorek, Gneiting)
- Add DOI reference to Rasmussen's book in refs.bib
- Safe optimization with GPJax
- Spec: xarray bridge — from_xarray / GridSpec round trip (pre-v1.0)
- Add functionality for MAP estimation of parameters
- `DualVariationalGaussian` can leave the PD cone / NaN under plain `fit()` despite `dual_elbo` docstring calling it valid
- Docs
- Python not yet supported