diff --git a/openTSNE/quad_tree.pyx b/openTSNE/quad_tree.pyx
index 16720aae..08bae6a0 100644
--- a/openTSNE/quad_tree.pyx
+++ b/openTSNE/quad_tree.pyx
@@ -124,7 +124,7 @@ cdef void split_node(Node * node):
     PyMem_Free(new_center)
 
 
-cdef inline bint is_duplicate(Node * node, double * point, double duplicate_eps=1e-6) nogil:
+cdef inline bint is_duplicate(Node * node, double * point, double duplicate_eps=1e-16) nogil:
     cdef Py_ssize_t d
     for d in range(node.n_dims):
         if fabs(node.center_of_mass[d] - point[d]) >= duplicate_eps:
diff --git a/tests/test_correctness.py b/tests/test_correctness.py
index 1be5ad4c..5e1f1759 100644
--- a/tests/test_correctness.py
+++ b/tests/test_correctness.py
@@ -318,3 +318,18 @@ def test_spectral_agreement_with_sklearn(self):
         np.testing.assert_almost_equal(
             np.abs(np.corrcoef(embedding1[:,1], embedding2[:,1])[0,1]), 1
         )
+
+
+class TestEarlyExaggerationCollapse(unittest.TestCase):
+    """In some cases, the BH implementation was producing a collapsed embedding
+    for all data points. For more information, see #233, #234."""
+    def test_early_exaggeration_does_not_collapse(self):
+        n_samples = [100, 150, 200]
+        n_dims = [5, 10, 20]
+
+        np.random.seed(42)
+        for n in n_samples:
+            for d in n_dims:
+                x = np.random.randn(n, d)
+                embedding = openTSNE.TSNE(random_state=42).fit(x)
+                self.assertGreater(np.max(np.abs(embedding)), 1e-8)