diff --git a/exercise-session-2.ipynb b/exercise-session-2.ipynb
index e9dea076c0e8d5f6435c469b0b4d39c50a23abce..43c03e3e4aa79503680047325fffa87812375781 100644
--- a/exercise-session-2.ipynb
+++ b/exercise-session-2.ipynb
@@ -32,6 +32,7 @@
     "import src.plotters as plotters\n",
     "import src.models as models\n",
     "import src.logic as logic\n",
+    "from src.utility import match_tracks_to_ground_truth, save_result\n",
     "# Get the necessary trajectories\n",
     "trajectories = get_ex2_trajectories()\n",
     "trajs = ['T1', 'T3', 'T5', 'T6'] # Select the trajectories to use\n",
@@ -156,7 +157,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from src.utility import match_tracks_to_ground_truth\n",
     "jpda_matches = match_tracks_to_ground_truth(jpda_confirmed_tracks, filtered_trajs)\n",
     "gnn_matches = match_tracks_to_ground_truth(gnn_confirmed_tracks, filtered_trajs)\n",
     "jpdaresult = dict(matches=jpda_matches, \n",
@@ -166,7 +166,9 @@
     "gnnresult = dict(matches=gnn_matches, \n",
     "                  tracks=gnn_tracks, \n",
     "                  confirmed_tracks=gnn_confirmed_tracks,\n",
-    "                  Y=Y)"
+    "                  Y=Y)\n",
+    "save_result('jpda_result_sim', jpdaresult)\n",
+    "save_result('gnn_result_sim', gnnresult)"
    ]
   },
   {
@@ -234,7 +236,7 @@
     "The filter was chosen as an EKF for simplicity (and it seemed to work fine).\n",
     "\n",
     "##### **Initialization**\n",
-    "The tracks were initialized at the measurement (converted to the positional domain) with a $0$ velocity. The initial uncertainty was set to $\\mathbf{P}_0=\\mathsc{diag}[100, 100, 1000, 1000]$ to account for the unknown initial velocity. The track score is initially set to $L_t=0$.\n"
+    "The tracks were initialized at the measurement (converted to the positional domain) with a $0$ velocity. The initial uncertainty was set to $\\mathbf{P}_0=\\mathrm{diag}[100, 100, 1000, 1000]$ to account for the unknown initial velocity. The track score is initially set to $L_t=0$.\n"
    ]
   },
   {
@@ -337,6 +339,17 @@
     "#### Comments\n",
     "Both the GNN and JPDA manage to keep both tracks the entire time. The GNN results in two \"U\"-shaped tracks whereas the JPDA results in \"S\"-shaped tracks. Without more information, it is impossible to say which is correct. However, the JPDA tracker results in a smoother trajectory, probably because of the soft measurement assignments."
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "99bb7ff2-1b69-4468-b9d6-7590a4870863",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "save_result('jpda_result_myst', jpda_result)\n",
+    "save_result('gnn_result_myst', gnn_result)"
+   ]
   }
  ],
  "metadata": {