diff --git a/Project.toml b/Project.toml
index f3d633beb..47ee0d086 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,6 +1,6 @@
 name = "KernelFunctions"
 uuid = "ec8451be-7e33-11e9-00cf-bbf324bd1392"
-version = "0.10.36"
+version = "0.10.37"
 
 [deps]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
diff --git a/src/basekernels/matern.jl b/src/basekernels/matern.jl
index a1ae4dfcc..dcc35f6be 100644
--- a/src/basekernels/matern.jl
+++ b/src/basekernels/matern.jl
@@ -17,6 +17,10 @@ By default, ``d`` is the Euclidean metric ``d(x, x') = \\|x - x'\\|_2``.
 A Gaussian process with a Matérn kernel is ``\\lceil \\nu \\rceil - 1``-times
 differentiable in the mean-square sense.
 
+!!! note
+
+    Differentiation with respect to the order ν is not currently supported.
+
 See also: [`Matern12Kernel`](@ref), [`Matern32Kernel`](@ref), [`Matern52Kernel`](@ref)
 """
 struct MaternKernel{Tν<:Real,M} <: SimpleKernel
@@ -33,8 +37,11 @@ MaternKernel(; nu::Real=1.5, ν::Real=nu, metric=Euclidean()) = MaternKernel(ν,
 
 @functor MaternKernel
 
-@inline function kappa(κ::MaternKernel, d::Real)
-    result = _matern(only(κ.ν), d)
+@inline _get_ν(k::MaternKernel) = only(k.ν)
+ChainRulesCore.@non_differentiable _get_ν(k)  # work-around; should be "NotImplemented" rather than NoTangent
+
+@inline function kappa(k::MaternKernel, d::Real)
+    result = _matern(_get_ν(k), d)
     return ifelse(iszero(d), one(result), result)
 end
 
diff --git a/src/matrix/kernelkroneckermat.jl b/src/matrix/kernelkroneckermat.jl
index d83463efa..113d0f53d 100644
--- a/src/matrix/kernelkroneckermat.jl
+++ b/src/matrix/kernelkroneckermat.jl
@@ -14,7 +14,7 @@ where `D` is given by `dims`.
 
 !!! warning
 
-    Require `Kronecker.jl` and for `iskroncompatible(κ)` to return `true`.
+    Requires `Kronecker.jl` and for `iskroncompatible(κ)` to return `true`.
 """
 function kernelkronmat(κ::Kernel, X::AbstractVector{<:Real}, dims::Int)
     checkkroncompatible(κ)
diff --git a/test/basekernels/matern.jl b/test/basekernels/matern.jl
index 5a83de55b..025cb141b 100644
--- a/test/basekernels/matern.jl
+++ b/test/basekernels/matern.jl
@@ -4,18 +4,15 @@
     v1 = rand(rng, 3)
     v2 = rand(rng, 3)
     @testset "MaternKernel" begin
-        ν = 2.0
+        ν = 2.1
         k = MaternKernel(; ν=ν)
         matern(x, ν) = 2^(1 - ν) / gamma(ν) * (sqrt(2ν) * x)^ν * besselk(ν, sqrt(2ν) * x)
         @test MaternKernel(; nu=ν).ν == [ν]
         @test kappa(k, x) ≈ matern(x, ν)
         @test kappa(k, 0.0) == 1.0
-        @test kappa(MaternKernel(; ν=ν), x) == kappa(k, x)
         @test metric(MaternKernel()) == Euclidean()
         @test metric(MaternKernel(; ν=2.0)) == Euclidean()
         @test repr(k) == "Matern Kernel (ν = $(ν), metric = Euclidean(0.0))"
-        # test_ADs(x->MaternKernel(nu=first(x)),[ν])
-        @test_broken "All fails (because of logabsgamma for ForwardDiff and ReverseDiff and because of nu for Zygote)"
 
         k2 = MaternKernel(; ν=ν, metric=WeightedEuclidean(ones(3)))
         @test metric(k2) isa WeightedEuclidean
@@ -23,6 +20,8 @@
 
         # Standardised tests.
         TestUtils.test_interface(k, Float64)
+        test_ADs(() -> MaternKernel(; nu=ν))
+
         test_params(k, ([ν],))
     end
     @testset "Matern32Kernel" begin