video links

Author: bstriner

recitation-10/Pytorch GANs.ipynb

@@ -107,7 +107,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Wasserstein GAN with Gradient Penalty"
+    "# Wasserstein GAN with Gradient Penalty\n",
+    "\n",
+    "Here we see an improvement on traditional GAN that we discussed in lecture."
    ]
   },
   {
@@ -130,7 +132,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# WGAN-GP on CIFAR10"
+    "# WGAN-GP on CIFAR10\n",
+    "\n",
+    "For a slightly more complicated dataset, this example uses CIFAR10."
    ]
   },
   {
@@ -143,17 +147,19 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "source": [
+    "https://youtu.be/dAe-UcOfywE"
+   ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Conditional WGAN-GP on MNIST"
+    "# Conditional WGAN-GP on MNIST\n",
+    "\n",
+    "Here use use a conditional GAN to learn each digit."
    ]
   },
   {
@@ -166,11 +172,11 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "source": [
+    "https://youtu.be/_wuRRwujeHc"
+   ]
   }
  ],
  "metadata": {