Update Colab links.

thebuckleylab · Nov 25, 2024 · 1d1e961 · 1d1e961
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diff --git a/examples/discriminative_pc.ipynb b/examples/discriminative_pc.ipynb
@@ -6,7 +6,7 @@
    "source": [
     "# Discriminative PC on MNIST\n",
     "\n",
-    "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://github.com/thebuckleylab/jpc/blob/main/examples/discriminative_pc.ipynb)\n",
+    "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/thebuckleylab/jpc/blob/main/examples/discriminative_pc.ipynb)\n",
     "\n",
     "This notebook demonstrates how to train a neural network with predictive coding (PC) to discriminate or classify MNIST digits."
    ]
@@ -394,4 +394,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}
diff --git a/examples/hybrid_pc.ipynb b/examples/hybrid_pc.ipynb
@@ -6,7 +6,7 @@
    "source": [
     "# Hybrid PC on MNIST\n",
     "\n",
-    "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://github.com/thebuckleylab/jpc/blob/main/examples/hybrid_pc.ipynb)\n",
+    "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/thebuckleylab/jpc/blob/main/examples/hybrid_pc.ipynb)\n",
     "\n",
     "This notebook demonstrates how to train a hybrid predictive coding network that can both generate and classify MNIST digits."
    ]
@@ -462,4 +462,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}
diff --git a/examples/linear_net_theoretical_energy.ipynb b/examples/linear_net_theoretical_energy.ipynb
@@ -6,7 +6,7 @@
    "source": [
     "# Theoretical energy of deep linear networks\n",
     "\n",
-    "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://github.com/thebuckleylab/jpc/blob/main/examples/analytical_test.ipynb)"
+    "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/thebuckleylab/jpc/blob/main/examples/linear_net_theoretical_energy.ipynb)"
    ]
   },
   {
@@ -377,4 +377,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}
diff --git a/examples/supervised_generative_pc.ipynb b/examples/supervised_generative_pc.ipynb
@@ -6,7 +6,7 @@
    "source": [
     "# Generative PC on MNIST\n",
     "\n",
-    "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://github.com/thebuckleylab/jpc/blob/main/examples/generative_pc.ipynb)\n",
+    "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/thebuckleylab/jpc/blob/main/examples/supervised_generative_pc.ipynb)\n",
     "\n",
     "This notebook demonstrates how to train a neural network with predictive coding to generate MNIST digits."
    ]
@@ -438,4 +438,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}
diff --git a/examples/unsupervised_generative_pc.ipynb b/examples/unsupervised_generative_pc.ipynb
@@ -6,6 +6,8 @@
    "source": [
     "# Unsupervised generative PC on MNIST\n",
     "\n",
+    "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/thebuckleylab/jpc/blob/main/examples/unsupervised_generative_pc.ipynb)\n",
+    "\n",
     "This notebook demonstrates how to train a neural network with predictive coding to encode MNIST digits in an unsupervised manner."
    ]
   },
@@ -424,4 +426,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}