diff --git a/docs/src/concepts/interacting_fgs.md b/docs/src/concepts/interacting_fgs.md
index 597221e39..c458d3a99 100644
--- a/docs/src/concepts/interacting_fgs.md
+++ b/docs/src/concepts/interacting_fgs.md
@@ -153,6 +153,11 @@ getPPESuggested(fg, :l5)
 
 There are values for mean, max, or hybrid combinations.
 
+```@docs
+getPPE
+calcPPE
+```
+
 ## Getting Many Marginal Samples
 
 It is also possible to sample the above belief objects for more samples:
diff --git a/docs/src/principles/approxConvDensities.md b/docs/src/principles/approxConvDensities.md
index 28dc8a77b..73965fd55 100644
--- a/docs/src/principles/approxConvDensities.md
+++ b/docs/src/principles/approxConvDensities.md
@@ -126,7 +126,16 @@ hatX1 = manikde!(pts, ContinuousScalar)
 
 The functional object `X1` is now ready for other operations such as function evaluation or product computations discussed on [another principles page](http://www.juliarobotics.org/Caesar.jl/latest/principles/multiplyingDensities/).  The `ContinuousScalar` manifold is just the real line in Euclidean space, internally denoted as single element tuple `(:Euclid,)`.
 
-## A Handy ZMQ interface to Generic Convolutions
+## `approxDeconv`
+
+Analogous to a 'forward' convolution calculation, we can similarly approximate the inverse:
+```@docs
+approxDeconv
+```
+
+This feature is not yet as feature rich as the `approxConv` function, and also requires further work to improve the consistency of the calculation -- but none the less exists and is useful in many applications.
+
+## ZMQ Interface [WORK IN PROGRESS]
 
 > **NOTE** WIP on expanding ZMQ interface: