more edits on the SIR notebook

examples/SIR_PosteriorEstimation.ipynb

@@ -14,6 +14,7 @@
    "metadata": {},
    "source": [
     "## Table of Contents\n",
+    "\n",
     " * [Introduction](#introduction)\n",
     " * [Defining the Generative Model](#defining_the_generative)\n",
     "\t * [Prior](#prior)\n",
@@ -816,6 +817,14 @@
     "f = bf.diagnostics.plot_recovery(samples[\"parameters\"], test_sims[\"parameters\"])"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "e64f683b",
+   "metadata": {},
+   "source": [
+    "Interestingly, it seems that the parameters $\\theta_1 = \\mu$ and $\\theta_2 = D$ have not been learned properly as they are estimated roughly the same for every simulated datset used during testing. For some models, this might indicate that the the network training had partially failed; and we would have to train longer or adjust the network architecture. For this specific model, however, the reason is different: From the provided observables, these parameters are actually not identified so cannot be learned consistently, no matter the kind of approximator we would use. "
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "occupational-professor",