diff --git a/conda-envs/environment-test.yml b/conda-envs/environment-test.yml
index a1aa85c7e..450b46e30 100644
--- a/conda-envs/environment-test.yml
+++ b/conda-envs/environment-test.yml
@@ -3,7 +3,7 @@ channels:
 - conda-forge
 - nodefaults
 dependencies:
-- pymc>=5.20
+- pymc>=5.21
 - pytest-cov>=2.5
 - pytest>=3.0
 - dask
diff --git a/conda-envs/windows-environment-test.yml b/conda-envs/windows-environment-test.yml
index 1d1eb7745..d2a3e8934 100644
--- a/conda-envs/windows-environment-test.yml
+++ b/conda-envs/windows-environment-test.yml
@@ -10,7 +10,7 @@ dependencies:
 - xhistogram
 - statsmodels
 - numba<=0.60.0
-- pymc>=5.20
+- pymc>=5.21
 - pip:
   - blackjax
   - scikit-learn
diff --git a/pymc_extras/statespace/core/statespace.py b/pymc_extras/statespace/core/statespace.py
index 2590dd53a..d5d131d80 100644
--- a/pymc_extras/statespace/core/statespace.py
+++ b/pymc_extras/statespace/core/statespace.py
@@ -707,7 +707,7 @@ def _insert_random_variables(self):
         with pymc_model:
             for param_name in self.param_names:
                 param = getattr(pymc_model, param_name, None)
-                if param:
+                if param is not None:
                     found_params.append(param.name)
 
         missing_params = list(set(self.param_names) - set(found_params))
@@ -746,7 +746,7 @@ def _insert_data_variables(self):
         with pymc_model:
             for data_name in data_names:
                 data = getattr(pymc_model, data_name, None)
-                if data:
+                if data is not None:
                     found_data.append(data.name)
 
         missing_data = list(set(data_names) - set(found_data))
diff --git a/pymc_extras/statespace/filters/distributions.py b/pymc_extras/statespace/filters/distributions.py
index d3b70c847..3d0ed44d6 100644
--- a/pymc_extras/statespace/filters/distributions.py
+++ b/pymc_extras/statespace/filters/distributions.py
@@ -62,29 +62,8 @@ class MvNormalSVD(MvNormal):
     A JAX MvNormal robust to low-rank covariance matrices
     """
 
-    rv_op = MvNormalSVDRV()
-
-
-try:
-    import jax.random
-
-    from pytensor.link.jax.dispatch.random import jax_sample_fn
-
-    @jax_sample_fn.register(MvNormalSVDRV)
-    def jax_sample_fn_mvnormal_svd(op, node):
-        def sample_fn(rng, size, dtype, *parameters):
-            rng_key = rng["jax_state"]
-            rng_key, sampling_key = jax.random.split(rng_key, 2)
-            sample = jax.random.multivariate_normal(
-                sampling_key, *parameters, shape=size, dtype=dtype, method="svd"
-            )
-            rng["jax_state"] = rng_key
-            return (rng, sample)
-
-        return sample_fn
-
-except ImportError:
-    pass
+    # TODO: Remove this entirely on next PyMC release; method will be exposed directly in MvNormal
+    rv_op = MvNormalSVDRV(method="svd")
 
 
 class LinearGaussianStateSpaceRV(SymbolicRandomVariable):
diff --git a/pyproject.toml b/pyproject.toml
index 17187a524..e16b3b389 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -20,6 +20,9 @@ filterwarnings =[
 
   # Warning coming from blackjax
   'ignore:jax\.tree_map is deprecated:DeprecationWarning',
+
+  # Ignore PyMC use of numpy.core
+  'ignore:numpy\.core\.numeric is deprecated:DeprecationWarning',
 ]
 
 [tool.coverage.report]
diff --git a/requirements.txt b/requirements.txt
index a4f00ee21..3a1f85ac8 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,3 +1,3 @@
-pymc>=5.20
+pymc>=5.21
 scikit-learn
 better-optimize