diff --git a/demo_poisson.ipynb b/demo_poisson.ipynb
index c817ad6a5d51abcfd8fd51a78db051bcb8545a20..72eedb410dce04a438866a0924af5d0dcd8c2f2c 100644
--- a/demo_poisson.ipynb
+++ b/demo_poisson.ipynb
@@ -28,7 +28,7 @@
     "from utils import plot_2D, load_psf, geovi_sampling, plot_posterior\n",
     "\n",
     "ift.random.push_sseq_from_seed(42)\n",
-    "evidences = []"
+    "evidences = np.zeros(3)"
    ]
   },
   {
@@ -74,7 +74,7 @@
     "\n",
     "\n",
     "print(evidence)\n",
-    "evidences += [evidence, ]"
+    "evidences[0] = evidence"
    ]
   },
   {
@@ -88,7 +88,7 @@
     "# Inference model 2\n",
     "\n",
     "\n",
-    "evidences += [evidence, ]"
+    "evidences[1] = evidence"
    ]
   },
   {
@@ -149,7 +149,7 @@
    "source": [
     "# Inference model 3\n",
     "\n",
-    "evidences += [evidence, ]"
+    "evidences[2] = evidence"
    ]
   },
   {
diff --git a/demo_poisson_solution.ipynb b/demo_poisson_solution.ipynb
index 52055b887a07ac8dc324bbe3aa49821ffcdc681e..2e0cbafb45bf0cb5efe354669a82b5665cd62a79 100644
--- a/demo_poisson_solution.ipynb
+++ b/demo_poisson_solution.ipynb
@@ -28,7 +28,7 @@
     "from utils import plot_2D, load_psf, geovi_sampling, plot_posterior\n",
     "\n",
     "ift.random.push_sseq_from_seed(42)\n",
-    "evidences = []"
+    "evidences = np.zeros(3)"
    ]
   },
   {
@@ -84,7 +84,7 @@
     "samples, evidence = geovi_sampling(likelihood @ model1)\n",
     "plot_2D(samples.average(model1).val, 'model1 posterior mean')\n",
     "print(evidence)\n",
-    "evidences += [evidence, ]"
+    "evidences[0] = evidence"
    ]
   },
   {
@@ -100,7 +100,7 @@
     "samples, evidence = geovi_sampling(likelihood @ model2)\n",
     "plot_2D(samples.average(model2).val, 'model2 posterior mean')\n",
     "print(evidence)\n",
-    "evidences += [evidence, ]"
+    "evidences[1] = evidence"
    ]
   },
   {
@@ -110,7 +110,7 @@
    "outputs": [],
    "source": [
     "# Compare evidence\n",
-    "print(evidences)"
+    "print(evidences[:2])"
    ]
   },
   {
@@ -169,7 +169,7 @@
     "samples, evidence = geovi_sampling(likelihood @ model3)\n",
     "plot_2D(samples.average(model3).val, 'model3 posterior mean')\n",
     "print(evidence)\n",
-    "evidences += [evidence, ]"
+    "evidences[2] = evidence"
    ]
   },
   {