From 87d8ce2da0f082e4ab8f2b9d030c66a152bc8eda Mon Sep 17 00:00:00 2001
From: Jeremy Teitelbaum <jeremy.teitelbaum@uconn.edu>
Date: Thu, 5 Jul 2018 15:24:09 -0400
Subject: [PATCH] dropped old jax_gl directory

---
 jax_gl/README.md      |  3 --
 jax_gl/Untitled.ipynb | 83 -------------------------------------------
 jax_gl/graph.tex      | 29 ---------------
 jax_gl/graph.tex~     | 11 ------
 4 files changed, 126 deletions(-)
 delete mode 100644 jax_gl/README.md
 delete mode 100644 jax_gl/Untitled.ipynb
 delete mode 100644 jax_gl/graph.tex
 delete mode 100644 jax_gl/graph.tex~

diff --git a/jax_gl/README.md b/jax_gl/README.md
deleted file mode 100644
index ed90f12..0000000
--- a/jax_gl/README.md
+++ /dev/null
@@ -1,3 +0,0 @@
-This work is obsolete and superseded by **graphE**.
-
-
diff --git a/jax_gl/Untitled.ipynb b/jax_gl/Untitled.ipynb
deleted file mode 100644
index 7a6c272..0000000
--- a/jax_gl/Untitled.ipynb
+++ /dev/null
@@ -1,83 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sklearn.neural_network import MLPClassifier"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "X=np.array([1,0,0,1])\n",
-    "X.shape=(2,2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[1, 0],\n",
-       "       [0, 1]])"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "clf=MLPClassifier(solver='lbfgs',alpha=.0001,hidden_layer_sizes=())"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.6"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/jax_gl/graph.tex b/jax_gl/graph.tex
deleted file mode 100644
index 4fb92a6..0000000
--- a/jax_gl/graph.tex
+++ /dev/null
@@ -1,29 +0,0 @@
-\documentclass{beamer}
-\begin{document}
-\begin{frame}
-\begin{center}
-Overview of \\
-Section 4.2.1: DL based Graph Embedding with Random Walk \\
-from \\
-\textit{A comprehensive survey of graph embedding: problems, techniques, and applications} \\
-\textit{Cai, et. al.} \\
-\textit{IEEE Transactions on Knowledge and Data Engineering, Sept. 2017} \\
-\end{center}
-
-Jeremy Teitelbaum \\
-July, 2018
-
-\end{frame}
-\begin{frame}{Context}
-\begin{problem}
-Given a finite graph $G$, find an embedding of $G$ into a relatively low dimensional Euclidean space in a way that captures
-relevant information about the structure of the graph.
-\end{problem}
-\bigskip\noindent
-\textbf{Deep Learning} algorithms in general are typically based on neural networks and are characterized by non-linearity and hierarchical structure.  
-
-\bigskip\noindent
-Deep learning techniques for graph embedding sample structure from a large graph and apply techniques arising from
-natural language processing to those samples to construct an embedding.
-\end{frame}
-\end{document}
\ No newline at end of file
diff --git a/jax_gl/graph.tex~ b/jax_gl/graph.tex~
deleted file mode 100644
index eb8a43f..0000000
--- a/jax_gl/graph.tex~
+++ /dev/null
@@ -1,11 +0,0 @@
-\documentclass{beamer}
-\begin{document}
-\begin{frame}
-\begin{center}
-DL based Graph Embedding with Random Walk \\
-from \\
-\texit{A comprehensive survey of graph embedding: problems, techniques, and applications} \\
-\textit{by Cai, et. al.}
-\textit{IEEE Transactions on Knowledge and Data Engineering, Sept. 2017}
-\end{frame}
-\end{document}
\ No newline at end of file