From e947b261f86c4739639af6e0bb187ec409dca056 Mon Sep 17 00:00:00 2001 From: udlbook <110402648+udlbook@users.noreply.github.com> Date: Mon, 4 Mar 2024 12:26:07 -0500 Subject: [PATCH] Created using Colaboratory --- Notebooks/Chap18/18_1_Diffusion_Encoder.ipynb | 21 +++++++++---------- 1 file changed, 10 insertions(+), 11 deletions(-) diff --git a/Notebooks/Chap18/18_1_Diffusion_Encoder.ipynb b/Notebooks/Chap18/18_1_Diffusion_Encoder.ipynb index 17656de..4824fcf 100644 --- a/Notebooks/Chap18/18_1_Diffusion_Encoder.ipynb +++ b/Notebooks/Chap18/18_1_Diffusion_Encoder.ipynb @@ -3,8 +3,8 @@ { "cell_type": "markdown", "metadata": { - "colab_type": "text", - "id": "view-in-github" + "id": "view-in-github", + "colab_type": "text" }, "source": [ "\"Open" @@ -405,11 +405,11 @@ "\n", " # TODO Write this function\n", " # 1. For each x (value in x_plot_vals):\n", - " # 2. Compute the mean and variance of the diffusion kernel at time t\n", - " # 3. Compute pdf of this Gaussian at every x_plot_val\n", - " # 4. Weight Gaussian by probability at position x and by 0.01 to componensate for bin size\n", - " # 5. Accumulate weighted Gaussian in marginal at time t.\n", - " # 6. Multiply result by 0.01 to compensate for bin size\n", + " # 2. Compute the mean and variance of the diffusion kernel at time t\n", + " # 3. Compute pdf of this Gaussian at every x_plot_val\n", + " # 4. Weight Gaussian by probability at position x and by 0.01 to componensate for bin size\n", + " # 5. Accumulate weighted Gaussian in marginal at time t.\n", + "\n", " # Replace this line:\n", " marginal_at_time_t = marginal_at_time_t\n", "\n", @@ -454,9 +454,8 @@ ], "metadata": { "colab": { - "authorship_tag": "ABX9TyMpC8kgLnXx0XQBtwNAQ4jJ", - "include_colab_link": true, - "provenance": [] + "provenance": [], + "include_colab_link": true }, "kernelspec": { "display_name": "Python 3", @@ -468,4 +467,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} +} \ No newline at end of file