diff --git a/funsor/delta.py b/funsor/delta.py
index d4582e18a..5102d384f 100644
--- a/funsor/delta.py
+++ b/funsor/delta.py
@@ -27,7 +27,7 @@ class Delta(Funsor):
     Normalized delta distribution binding a single variable.
 
     :param str name: Name of the bound variable.
-    :param Funsor value: Value of the bound variable.
+    :param Funsor point: Value of the bound variable.
     :param Funsor log_density: Optional log density to be added when evaluating
         at a point. This is needed to make :class:`Delta` closed under
         differentiable substitution.
diff --git a/test/test_distributions.py b/test/test_distributions.py
index ae1266249..622a0678a 100644
--- a/test/test_distributions.py
+++ b/test/test_distributions.py
@@ -8,6 +8,7 @@
 
 import funsor
 import funsor.distributions as dist
+from funsor.delta import Delta
 from funsor.domains import bint, reals
 from funsor.gaussian import Gaussian
 from funsor.terms import Variable
@@ -80,6 +81,14 @@ def delta(v, log_density, value):
         assert_close(actual, expected)
 
 
+def test_delta_delta():
+    v = Variable('v', reals(2))
+    point = Tensor(torch.randn(2))
+    log_density = Tensor(torch.tensor(0.5))
+    d = dist.Delta(point, log_density, v)
+    assert d is Delta('v', point, log_density)
+
+
 def test_normal_defaults():
     loc = Variable('loc', reals())
     scale = Variable('scale', reals())