Added Kronecker GP PR features

Author: jordan-melendez

RELEASE-NOTES.md

@@ -5,14 +5,19 @@
 ### New features
 
 - Add `logit_p` keyword to `pm.Bernoulli`, so that users can specify the logit of the success probability. This is faster and more stable than using `p=tt.nnet.sigmoid(logit_p)`.
-- Add `random` keyword to `pm.DensityDist` thus enabling users to pass custom random method which in turn makes sampling from a `DensityDist` possible. 
+- Add `random` keyword to `pm.DensityDist` thus enabling users to pass custom random method which in turn makes sampling from a `DensityDist` possible.
 - Effective sample size computation is updated. The estimation uses Geyer's initial positive sequence, which no longer truncates the autocorrelation series inaccurately. `pm.diagnostics.effective_n` now can reports N_eff>N.
+- Added `KroneckerNormal` distribution and a corresponding `MarginalKron`
+  Gaussian Process implementation for efficient inference, along with
+  lower-level functions such as `cartesian` and `kronecker` products.
+- Added `Coregion` covariance function.
 
 
 ### Fixes
 
 - `VonMises` does not overflow for large values of kappa. i0 and i1 have been removed and we now use log_i0 to compute the logp.
 
+
 ### Deprecations
 
 - DIC and BPIC calculations have been removed