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diff --git a/machine-learning-hats/figures/toy_graph.png b/machine-learning-hats/figures/toy_graph.png
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diff --git a/machine-learning-hats/notebooks/4-gnn-cora.ipynb b/machine-learning-hats/notebooks/4-gnn-cora.ipynb
index b1259d1..a7bed93 100644
--- a/machine-learning-hats/notebooks/4-gnn-cora.ipynb
+++ b/machine-learning-hats/notebooks/4-gnn-cora.ipynb
@@ -5,11 +5,13 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "# Graph Neural Network (GNN) with PyTorch Geometric\n",
+    "\n",
     "The contents of this tutorial are heavily adapted from a similar one make by [Savannah Thais](https://github.com/savvy379) using tensorflow and keras.\n",
     "\n",
-    "A graph $G=(N,E)$, comprising nodes $N$ and edges $E$, is a versatile mathematical structure that can represent various data such as molecules, social networks, transportation systems, etc. Nodes and edges may have associated features like geometric or non-geometric information. Graphs can be directed or undirected, and GNNs, with their ability to handle graphs of varying sizes, are well-suited for diverse applications including High Energy Physics (HEP). \n",
+    "A graph $G=(N,E)$, comprising of nodes $N$ and edges $E$, is a versatile mathematical structure that can represent various data such as molecules, social networks, transportation systems, etc. Nodes and edges may have associated features like geometric or non-geometric information. Graphs can be directed or undirected, and GNNs, with their ability to handle graphs of varying shapes and sizes, are well-suited for diverse applications including High Energy Physics (HEP). \n",
     "\n",
-    "![](toy_graph.png)"
+    "![](../figures/toy_graph.png)"
    ]
   },
   {
@@ -19,14 +21,14 @@
    "source": [
     "GNNs, particularly Graph Convolutional Networks (GCNs), re-embed graph edges and nodes by applying convolution operations to node neighborhoods, unlike the fixed data tensors used in conventional CNNs. This process, termed as \"Message Passing,\" constructs messages by combining information from neighboring nodes, then passes them to target nodes to update features. The entire graph is thus transformed, incorporating valuable information within each node. The convolved graph is often further processed for classification or regression on individual elements or the entire graph. This structure can also be applied to update edge features.\n",
     "\n",
-    "![](message_passing.png)"
+    "![](../figures/message_passing.png)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "![](graph_eq.png)\n",
+    "![](../figures/graph_eq.png)\n",
     "\n",
     "- Initial Embedding: Each node $v$ starts with an initial embedding $h_v^0$, representing the original node features.\n",
     "- Neighbors: For each node $v$, the neighboring nodes are represented as $N(v)$.\n",
@@ -44,9 +46,9 @@
     "id": "xG3U6QlQ9LlN"
    },
    "source": [
-    "# Graph Neural Network (GNN) with PyTorch Geometric\n",
+    "## Code!\n",
     "\n",
-    "In this tutorial, we will implement a Graph Neural Network (GNN) using PyTorch Geometric. We'll use the Cora dataset, which consists of scientific publications as nodes and citation links as edges.\n",
+    "In this tutorial, we will implement a Graph Neural Network (GNN) using PyTorch Geometric. We'll perform node classification on the Cora dataset, which consists of scientific publications as nodes and citation links as edges.\n",
     "\n",
     "The steps in this tutorial include:\n",
     "1. Installing PyTorch Geometric\n",
@@ -60,41 +62,64 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 10,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/"
     },
     "id": "YT9VFkkH49uK",
-    "outputId": "2abce9d8-f77e-4643-e2a7-73a69c999880"
+    "outputId": "2abce9d8-f77e-4643-e2a7-73a69c999880",
+    "scrolled": true
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Requirement already satisfied: torch_geometric in /usr/local/lib/python3.10/dist-packages (2.3.1)\n",
-      "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from torch_geometric) (4.66.0)\n",
-      "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from torch_geometric) (1.23.5)\n",
-      "Requirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from torch_geometric) (1.10.1)\n",
-      "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch_geometric) (3.1.2)\n",
-      "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from torch_geometric) (2.31.0)\n",
-      "Requirement already satisfied: pyparsing in /usr/local/lib/python3.10/dist-packages (from torch_geometric) (3.1.1)\n",
-      "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.10/dist-packages (from torch_geometric) (1.2.2)\n",
-      "Requirement already satisfied: psutil>=5.8.0 in /usr/local/lib/python3.10/dist-packages (from torch_geometric) (5.9.5)\n",
-      "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch_geometric) (2.1.3)\n",
-      "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->torch_geometric) (3.2.0)\n",
-      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->torch_geometric) (3.4)\n",
-      "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->torch_geometric) (2.0.4)\n",
-      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->torch_geometric) (2023.7.22)\n",
-      "Requirement already satisfied: joblib>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-learn->torch_geometric) (1.3.2)\n",
-      "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn->torch_geometric) (3.2.0)\n"
+      "Requirement already satisfied: torch_geometric in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (2.3.1)\n",
+      "Requirement already satisfied: tqdm in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from torch_geometric) (4.65.0)\n",
+      "Requirement already satisfied: numpy in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from torch_geometric) (1.25.1)\n",
+      "Requirement already satisfied: scipy in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from torch_geometric) (1.11.1)\n",
+      "Requirement already satisfied: jinja2 in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from torch_geometric) (3.1.2)\n",
+      "Requirement already satisfied: requests in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from torch_geometric) (2.31.0)\n",
+      "Requirement already satisfied: pyparsing in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from torch_geometric) (3.0.4)\n",
+      "Requirement already satisfied: scikit-learn in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from torch_geometric) (1.3.0)\n",
+      "Requirement already satisfied: psutil>=5.8.0 in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from torch_geometric) (5.9.5)\n",
+      "Requirement already satisfied: MarkupSafe>=2.0 in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from jinja2->torch_geometric) (2.1.3)\n",
+      "Requirement already satisfied: charset-normalizer<4,>=2 in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from requests->torch_geometric) (3.2.0)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from requests->torch_geometric) (3.4)\n",
+      "Requirement already satisfied: urllib3<3,>=1.21.1 in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from requests->torch_geometric) (2.0.3)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from requests->torch_geometric) (2023.5.7)\n",
+      "Requirement already satisfied: joblib>=1.1.1 in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from scikit-learn->torch_geometric) (1.3.1)\n",
+      "Requirement already satisfied: threadpoolctl>=2.0.0 in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from scikit-learn->torch_geometric) (3.2.0)\n",
+      "Collecting torchviz\n",
+      "  Downloading torchviz-0.0.2.tar.gz (4.9 kB)\n",
+      "  Preparing metadata (setup.py) ... \u001b[?25ldone\n",
+      "\u001b[?25hRequirement already satisfied: torch in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from torchviz) (2.0.1)\n",
+      "Collecting graphviz (from torchviz)\n",
+      "  Downloading graphviz-0.20.1-py3-none-any.whl (47 kB)\n",
+      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m47.0/47.0 kB\u001b[0m \u001b[31m858.8 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0ma \u001b[36m0:00:01\u001b[0m\n",
+      "\u001b[?25hRequirement already satisfied: filelock in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from torch->torchviz) (3.12.2)\n",
+      "Requirement already satisfied: typing-extensions in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from torch->torchviz) (4.7.1)\n",
+      "Requirement already satisfied: sympy in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from torch->torchviz) (1.12)\n",
+      "Requirement already satisfied: networkx in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from torch->torchviz) (3.1)\n",
+      "Requirement already satisfied: jinja2 in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from torch->torchviz) (3.1.2)\n",
+      "Requirement already satisfied: MarkupSafe>=2.0 in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from jinja2->torch->torchviz) (2.1.3)\n",
+      "Requirement already satisfied: mpmath>=0.19 in /uscms/home/aaportel/nobackup/mamba/envs/ml/lib/python3.11/site-packages (from sympy->torch->torchviz) (1.3.0)\n",
+      "Building wheels for collected packages: torchviz\n",
+      "  Building wheel for torchviz (setup.py) ... \u001b[?25ldone\n",
+      "\u001b[?25h  Created wheel for torchviz: filename=torchviz-0.0.2-py3-none-any.whl size=4131 sha256=3593429a9b86799f5b41f3251aeb3d1d55045ea88a70f3ac8410df2eb6c59242\n",
+      "  Stored in directory: /uscms/homes/a/aaportel/.cache/pip/wheels/5a/d0/3f/b7014553eb74f12892b7d9b69c6083044564712d10fde8dfdc\n",
+      "Successfully built torchviz\n",
+      "Installing collected packages: graphviz, torchviz\n",
+      "Successfully installed graphviz-0.20.1 torchviz-0.0.2\n"
      ]
     }
    ],
    "source": [
     "# Step 1: Install PyTorch Geometric\n",
-    "!pip install torch_geometric"
+    "!pip install torch_geometric\n",
+    "!pip install torchviz"
    ]
   },
   {
@@ -135,11 +160,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {
     "id": "LyIUbDSa45Jo"
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading https://github.com/kimiyoung/planetoid/raw/master/data/ind.cora.x\n",
+      "Downloading https://github.com/kimiyoung/planetoid/raw/master/data/ind.cora.tx\n",
+      "Downloading https://github.com/kimiyoung/planetoid/raw/master/data/ind.cora.allx\n",
+      "Downloading https://github.com/kimiyoung/planetoid/raw/master/data/ind.cora.y\n",
+      "Downloading https://github.com/kimiyoung/planetoid/raw/master/data/ind.cora.ty\n",
+      "Downloading https://github.com/kimiyoung/planetoid/raw/master/data/ind.cora.ally\n",
+      "Downloading https://github.com/kimiyoung/planetoid/raw/master/data/ind.cora.graph\n",
+      "Downloading https://github.com/kimiyoung/planetoid/raw/master/data/ind.cora.test.index\n",
+      "Processing...\n",
+      "Done!\n"
+     ]
+    }
+   ],
    "source": [
     "# Load Cora dataset\n",
     "dataset = Planetoid(root='/tmp/Cora', name='Cora')\n",
@@ -157,7 +199,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/"
@@ -172,7 +214,7 @@
        "Data(x=[2708, 1433], edge_index=[2, 10556], y=[2708], train_mask=[2708], val_mask=[2708], test_mask=[2708])"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -183,7 +225,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/"
@@ -236,6 +278,48 @@
     "print(\"test_mask: \\n\", data.test_mask, '\\n')"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also visualize the dataset using `networkx`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x1200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import networkx as nx\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "# Convert to networkx graph\n",
+    "G = nx.DiGraph()\n",
+    "for i, j in zip(*data.edge_index):\n",
+    "    G.add_edge(i.item(), j.item())\n",
+    "\n",
+    "# Draw a subset of the graph (e.g., first 300 nodes)\n",
+    "subset_nodes = list(G.nodes)[:300]\n",
+    "subset_graph = G.subgraph(subset_nodes)\n",
+    "\n",
+    "plt.figure(figsize=(12, 12))\n",
+    "nx.draw(subset_graph, with_labels=False, node_size=10)\n",
+    "plt.title('Visualization of a Subset of the Cora Graph')\n",
+    "plt.show()\n"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -451,9 +535,9 @@
    "provenance": []
   },
   "kernelspec": {
-   "display_name": "machine-learning-hats",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "machine-learning-hats"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {