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remove table from readme, not really informative there (#40)
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‎README.md‎

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@@ -100,189 +100,6 @@ We provide larger datasets that should be used instead:
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</details>
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## Benchmarking snapshot
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Here is an example benchmark one can generate with this library using multiple different models and datasets. The details of the generation of this benchmark are given in our paper.
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<table>
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<thead>
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<tr>
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<th rowspan="2">Dataset</th>
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<th rowspan="2">Model</th>
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<th rowspan="2">VUN (↑)</th>
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<th rowspan="2">PGD (↓)</th>
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<th colspan="6">PGD subscores</th>
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</tr>
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<tr>
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<th>Clust. (↓)</th>
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<th>Deg. (↓)</th>
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<th>GIN (↓)</th>
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<th>Orb5. (↓)</th>
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<th>Orb4. (↓)</th>
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<th>Eig. (↓)</th>
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</tr>
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</thead>
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<tbody>
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<!-- Planar-L -->
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<tr><td rowspan="4"><b>Planar-L</b></td>
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<td>AutoGraph</td>
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<td><i>85.1</i></td>
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<td><b>34.0 ± 1.8</b></td>
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<td><b>7.0 ± 2.9</b></td>
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<td><b>7.8 ± 3.2</b></td>
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<td><b>8.8 ± 3.0</b></td>
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<td><b>34.0 ± 1.8</b></td>
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<td><b>28.5 ± 1.5</b></td>
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<td><b>26.9 ± 2.3</b></td></tr>
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<tr><td>DiGress</td>
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<td>80.1</td>
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<td>45.2 ± 1.8</td>
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<td>24.8 ± 2.0</td>
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<td>23.3 ± 1.2</td>
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<td><i>29.0 ± 1.1</i></td>
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<td>45.2 ± 1.8</td>
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<td><i>40.3 ± 1.8</i></td>
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<td>39.4 ± 2.0</td></tr>
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<tr><td>GRAN</td>
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<td>1.6</td>
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<td>99.7 ± 0.2</td>
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<td>99.3 ± 0.2</td>
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<td>98.3 ± 0.3</td>
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<td>98.3 ± 0.3</td>
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<td>99.7 ± 0.1</td>
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<td>99.2 ± 0.2</td>
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<td>98.5 ± 0.4</td></tr>
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<tr><td>ESGG</td>
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<td><b>93.9</b></td>
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<td><i>45.0 ± 1.4</i></td>
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<td><i>10.9 ± 3.2</i></td>
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<td><i>21.7 ± 3.0</i></td>
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<td>32.9 ± 2.2</td>
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<td><i>45.0 ± 1.4</i></td>
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<td>42.8 ± 1.9</td>
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<td><i>29.6 ± 1.6</i></td></tr>
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<!-- Lobster-L -->
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<tr><td rowspan="4"><b>Lobster-L</b></td>
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<td>AutoGraph</td>
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<td><i>83.1</i></td>
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<td><i>18.0 ± 1.6</i></td>
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<td>4.2 ± 1.9</td>
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<td><i>12.1 ± 1.6</i></td>
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<td><i>14.8 ± 1.5</i></td>
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<td><i>18.0 ± 1.6</i></td>
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<td><i>16.1 ± 1.6</i></td>
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<td><i>13.0 ± 1.1</i></td></tr>
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<tr><td>DiGress</td>
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<td><b>91.4</b></td>
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<td><b>3.2 ± 2.6</b></td>
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<td><i>2.0 ± 1.3</i></td>
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<td><b>1.2 ± 1.5</b></td>
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<td><b>2.3 ± 2.0</b></td>
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<td><b>3.0 ± 3.1</b></td>
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<td><b>4.5 ± 2.3</b></td>
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<td><b>1.3 ± 1.1</b></td></tr>
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<tr><td>GRAN</td>
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<td>41.3</td>
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<td>85.4 ± 0.5</td>
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<td>20.8 ± 1.1</td>
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<td>77.1 ± 1.2</td>
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<td>79.8 ± 0.6</td>
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<td>85.4 ± 0.5</td>
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<td>85.0 ± 0.6</td>
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<td>69.8 ± 1.2</td></tr>
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<tr><td>ESGG</td>
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<td>70.9</td>
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<td>69.9 ± 0.6</td>
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<td><b>0.0 ± 0.0</b></td>
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<td>63.4 ± 1.1</td>
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<td>66.8 ± 1.0</td>
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<td>69.9 ± 0.6</td>
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<td>66.0 ± 0.6</td>
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<td>51.7 ± 1.8</td></tr>
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<!-- SBM-L -->
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<tr><td rowspan="4"><b>SBM-L</b></td>
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<td>AutoGraph</td>
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<td><b>85.6</b></td>
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<td><b>5.6 ± 1.5</b></td>
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<td><b>0.3 ± 0.6</b></td>
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<td><b>6.2 ± 1.4</b></td>
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<td><b>6.3 ± 1.3</b></td>
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<td><b>3.2 ± 2.2</b></td>
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<td><b>4.4 ± 2.0</b></td>
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<td><b>2.5 ± 2.2</b></td></tr>
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<tr><td>DiGress</td>
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<td><i>73.0</i></td>
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<td><i>17.4 ± 2.3</i></td>
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<td><i>5.7 ± 2.8</i></td>
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<td><i>8.2 ± 3.3</i></td>
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<td><i>13.8 ± 1.7</i></td>
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<td><i>17.4 ± 2.3</i></td>
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<td><i>14.8 ± 2.5</i></td>
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<td><i>8.7 ± 3.0</i></td></tr>
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<tr><td>GRAN</td>
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<td>21.4</td>
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<td>69.1 ± 1.4</td>
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<td>50.2 ± 1.9</td>
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<td>58.6 ± 1.4</td>
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<td>69.1 ± 1.4</td>
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<td>65.7 ± 1.3</td>
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<td>62.8 ± 1.3</td>
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<td>55.9 ± 1.5</td></tr>
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<tr><td>ESGG</td>
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<td>10.4</td>
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<td>99.4 ± 0.2</td>
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<td>97.9 ± 0.5</td>
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<td>97.5 ± 0.6</td>
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<td>98.3 ± 0.4</td>
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<td>96.8 ± 0.4</td>
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<td>89.2 ± 0.7</td>
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<td>99.4 ± 0.2</td></tr>
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<!-- Proteins -->
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<tr><td rowspan="4"><b>Proteins</b></td>
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<td>AutoGraph</td>
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<td>–</td>
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<td><b>67.7 ± 7.4</b></td>
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<td><i>47.7 ± 5.7</i></td>
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<td><i>31.5 ± 8.5</i></td>
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<td><i>45.3 ± 5.1</i></td>
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<td><b>67.7 ± 7.4</b></td>
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<td><b>47.4 ± 7.0</b></td>
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<td>53.2 ± 6.9</td></tr>
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<tr><td>DiGress</td>
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<td>–</td>
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<td>88.1 ± 3.1</td>
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<td><b>36.1 ± 4.3</b></td>
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<td><b>29.2 ± 5.0</b></td>
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<td><b>23.2 ± 5.3</b></td>
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<td>88.1 ± 3.1</td>
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<td><i>60.8 ± 3.6</i></td>
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<td><b>23.4 ± 11.8</b></td></tr>
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<tr><td>GRAN</td>
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<td>–</td>
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<td>89.7 ± 2.7</td>
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<td>86.0 ± 2.0</td>
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<td>70.6 ± 3.1</td>
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<td>71.5 ± 3.0</td>
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<td>90.4 ± 2.4</td>
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<td>84.4 ± 3.3</td>
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<td>76.7 ± 4.7</td></tr>
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<tr><td>ESGG</td>
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<td>–</td>
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<td><i>79.2 ± 4.3</i></td>
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<td>58.2 ± 3.6</td>
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<td>54.0 ± 3.6</td>
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<td>57.4 ± 4.1</td>
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<td><i>80.2 ± 3.1</i></td>
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<td>72.5 ± 3.0</td>
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<td><i>24.3 ± 11.0</i></td></tr>
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</tbody>
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</table>
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## Tutorial
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Our [demo script](polygraph_demo.py) showcases some features of our library in action.

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