Commit: d1332adb54661bf8303a1acb231b39c808c6568c

Number of runs per experiment: 1

Very concise format

+--------------------+-------------------------+-------------------------+-------------------------+-------------------------+-------------------------+
|                    | citeseer                | cora                    | cornell                 | pubmed                  | facebook                |
|                    | 140506746068368         | 140506746094160         | 140505409681360         | 140505409778448         | 140505409770448         |
+====================+=========================+=========================+=========================+=========================+=========================+
| gcn                | val.best_acc  0.552±0.0 | val.best_acc  0.582±0.0 | val.best_acc  0.703±0.0 | val.best_acc  0.726±0.0 | val.best_acc  0.351±0.0 |
| mlp                | val.epoch     299.0±0.0 | val.epoch     299.0±0.0 | val.epoch     299.0±0.0 | val.epoch     299.0±0.0 | val.epoch     299.0±0.0 |
| adam ,lr:0.01      | test.acc      0.594±0.0 | test.acc      0.605±0.0 | test.acc      0.694±0.0 | test.acc      0.734±0.0 | test.acc      0.359±0.0 |
|                    | params        118726    | params        46119     | params        54693     | params        16131     | params        47391     |
+--------------------+-------------------------+-------------------------+-------------------------+-------------------------+-------------------------+
| gcn                | val.best_acc  0.712±0.0 | val.best_acc  0.788±0.0 | val.best_acc  0.432±0.0 | val.best_acc  0.788±0.0 | val.best_acc  0.49±0.0  |
| welling-normalized | val.epoch     299.0±0.0 | val.epoch     299.0±0.0 | val.epoch     299.0±0.0 | val.epoch     299.0±0.0 | val.epoch     299.0±0.0 |
| adam ,lr:0.01      | test.acc      0.712±0.0 | test.acc      0.813±0.0 | test.acc      0.444±0.0 | test.acc      0.793±0.0 | test.acc      0.517±0.0 |
|                    | params        118726    | params        46119     | params        54693     | params        16131     | params        47391     |
+--------------------+-------------------------+-------------------------+-------------------------+-------------------------+-------------------------+
| gcn                | val.best_acc  0.704±0.0 | val.best_acc  0.798±0.0 | val.best_acc  0.486±0.0 | val.best_acc  0.782±0.0 | val.best_acc  0.537±0.0 |
| welling-normalized | val.epoch     299.0±0.0 | val.epoch     299.0±0.0 | val.epoch     299.0±0.0 | val.epoch     299.0±0.0 | val.epoch     299.0±0.0 |
| adam ,lr:0.01-2    | test.acc      0.714±0.0 | test.acc      0.809±0.0 | test.acc      0.5±0.0   | test.acc      0.792±0.0 | test.acc      0.555±0.0 |
|                    | params        118918    | params        46343     | params        54853     | params        16227     | params        53503     |
+--------------------+-------------------------+-------------------------+-------------------------+-------------------------+-------------------------+

Slightly more verbose
+--------------------+-----------------------------------------+-----------------------------------------+--------------------------------------+-----------------------------------------+-----------------------------------------+
|                    | citeseer                                | cora                                    | cornell                              | pubmed                                  | facebook                                |
|                    | 140506746068368                         | 140506746094160                         | 140505409681360                      | 140505409778448                         | 140505409770448                         |
+====================+=========================================+=========================================+======================================+=========================================+=========================================+
| gcn                | train.loss    0.19±0.0    0.19,0.19     | train.loss    0.171±0.0  0.171,0.171    | train.loss    0.275±0.0  0.275,0.275 | train.loss    0.052±0.0  0.052,0.052    | train.loss    2.737±0.0  2.737,2.737    |
| mlp                | train.acc     0.992±0.0   0.992,0.992   | train.acc     0.993±0.0  0.993,0.993    | train.acc     0.964±0.0  0.964,0.964 | train.acc     1.0±0.0    1.0,1.0        | train.acc     0.38±0.0   0.38,0.38      |
| adam ,lr:0.01      | train.time    28.008±0.0  28.008,28.008 | train.time    9.446±0.0  9.446,9.446    | train.time    4.506±0.0  4.506,4.506 | train.time    27.8±0.0   27.8,27.8      | train.time    15.45±0.0  15.45,15.45    |
|                    | val.best_acc  0.552±0.0   0.552,0.552   | val.best_acc  0.582±0.0  0.582,0.582    | val.best_acc  0.703±0.0  0.703,0.703 | val.best_acc  0.726±0.0  0.726,0.726    | val.best_acc  0.351±0.0  0.351,0.351    |
|                    | val.epoch     299.0±0.0   299,299       | val.epoch     299.0±0.0  299,299        | val.epoch     299.0±0.0  299,299     | val.epoch     299.0±0.0  299,299        | val.epoch     299.0±0.0  299,299        |
|                    | test.loss     1.205±0.0   1.205,1.205   | test.loss     1.244±0.0  1.244,1.244    | test.loss     0.92±0.0   0.92,0.92   | test.loss     0.73±0.0   0.73,0.73      | test.loss     2.824±0.0  2.824,2.824    |
|                    | test.acc      0.594±0.0   0.594,0.594   | test.acc      0.605±0.0  0.605,0.605    | test.acc      0.694±0.0  0.694,0.694 | test.acc      0.734±0.0  0.734,0.734    | test.acc      0.359±0.0  0.359,0.359    |
|                    | params        118726                    | params        46119                     | params        54693                  | params        16131                     | params        47391                     |
+--------------------+-----------------------------------------+-----------------------------------------+--------------------------------------+-----------------------------------------+-----------------------------------------+
| gcn                | train.loss    0.227±0.0   0.227,0.227   | train.loss    0.172±0.0   0.172,0.172   | train.loss    0.838±0.0  0.838,0.838 | train.loss    0.1±0.0     0.1,0.1       | train.loss    2.132±0.0   2.132,2.132   |
| welling-normalized | train.acc     0.992±0.0   0.992,0.992   | train.acc     0.986±0.0   0.986,0.986   | train.acc     0.773±0.0  0.773,0.773 | train.acc     1.0±0.0     1.0,1.0       | train.acc     0.511±0.0   0.511,0.511   |
| adam ,lr:0.01      | train.time    27.817±0.0  27.817,27.817 | train.time    10.525±0.0  10.525,10.525 | train.time    4.942±0.0  4.942,4.942 | train.time    30.185±0.0  30.185,30.185 | train.time    17.402±0.0  17.402,17.402 |
|                    | val.best_acc  0.712±0.0   0.712,0.712   | val.best_acc  0.788±0.0   0.788,0.788   | val.best_acc  0.432±0.0  0.432,0.432 | val.best_acc  0.788±0.0   0.788,0.788   | val.best_acc  0.49±0.0    0.49,0.49     |
|                    | val.epoch     299.0±0.0   299,299       | val.epoch     299.0±0.0   299,299       | val.epoch     299.0±0.0  299,299     | val.epoch     299.0±0.0   299,299       | val.epoch     299.0±0.0   299,299       |
|                    | test.loss     0.944±0.0   0.944,0.944   | test.loss     0.703±0.0   0.703,0.703   | test.loss     1.352±0.0  1.352,1.352 | test.loss     0.554±0.0   0.554,0.554   | test.loss     2.177±0.0   2.177,2.177   |
|                    | test.acc      0.712±0.0   0.712,0.712   | test.acc      0.813±0.0   0.813,0.813   | test.acc      0.444±0.0  0.444,0.444 | test.acc      0.793±0.0   0.793,0.793   | test.acc      0.517±0.0   0.517,0.517   |
|                    | params        118726                    | params        46119                     | params        54693                  | params        16131                     | params        47391                     |
+--------------------+-----------------------------------------+-----------------------------------------+--------------------------------------+-----------------------------------------+-----------------------------------------+
| gcn                | train.loss    0.119±0.0   0.119,0.119   | train.loss    0.088±0.0   0.088,0.088   | train.loss    0.428±0.0  0.428,0.428 | train.loss    0.048±0.0   0.048,0.048   | train.loss    1.795±0.0   1.795,1.795   |
| welling-normalized | train.acc     1.0±0.0     1.0,1.0       | train.acc     1.0±0.0     1.0,1.0       | train.acc     0.9±0.0    0.9,0.9     | train.acc     1.0±0.0     1.0,1.0       | train.acc     0.553±0.0   0.553,0.553   |
| adam ,lr:0.01-2    | train.time    29.519±0.0  29.519,29.519 | train.time    10.675±0.0  10.675,10.675 | train.time    5.381±0.0  5.381,5.381 | train.time    29.837±0.0  29.837,29.837 | train.time    17.216±0.0  17.216,17.216 |
|                    | val.best_acc  0.704±0.0   0.704,0.704   | val.best_acc  0.798±0.0   0.798,0.798   | val.best_acc  0.486±0.0  0.486,0.486 | val.best_acc  0.782±0.0   0.782,0.782   | val.best_acc  0.537±0.0   0.537,0.537   |
|                    | val.epoch     299.0±0.0   299,299       | val.epoch     299.0±0.0   299,299       | val.epoch     299.0±0.0  299,299     | val.epoch     299.0±0.0   299,299       | val.epoch     299.0±0.0   299,299       |
|                    | test.loss     0.907±0.0   0.907,0.907   | test.loss     0.657±0.0   0.657,0.657   | test.loss     1.429±0.0  1.429,1.429 | test.loss     0.557±0.0   0.557,0.557   | test.loss     1.888±0.0   1.888,1.888   |
|                    | test.acc      0.714±0.0   0.714,0.714   | test.acc      0.809±0.0   0.809,0.809   | test.acc      0.5±0.0    0.5,0.5     | test.acc      0.792±0.0   0.792,0.792   | test.acc      0.555±0.0   0.555,0.555   |
|                    | params        118918                    | params        46343                     | params        54853                  | params        16227                     | params        53503                     |
+--------------------+-----------------------------------------+-----------------------------------------+--------------------------------------+-----------------------------------------+---