Event Sequence Forecasting on Twitter (test)
0.01Wasserstein DistanceRNN
Evaluation results
| Method | Links | ||
|---|---|---|---|
| RNN2023.11 | 0.01 | — | |
| TriTPP2023.11 | 0.01 | — | |
| ADD-THIN2023.11 | 0.01 | — | |
| Transformer2023.11 | 0.05 | — | |
| GD2023.11 | 0.07 | — | |
| ADD-THIN2023.11 | 1.48 | — | |
| ADD-THINAverage Seq. Length=14.9, Number of forecast windows=502023.11 | 1.48 | — | |
| RNN2023.11 | 2.04 | — | |
| RNNAverage Seq. Length=14.9, Number of forecast windows=502023.11 | 2.04 | — | |
| Transformer2023.11 | 2.09 | — | |
| TransformerAverage Seq. Length=14.9, Number of forecast windows=502023.11 | 2.09 | — | |
| GD2023.11 | 2.16 | — | |
| GDAverage Seq. Length=14.9, Number of forecast windows=502023.11 | 2.16 | — | |
| ADD-THINAverage Seq. Length=14.9, Forecast Windows=502023.11 | — | 0.69 | |
| GDAverage Seq. Length=14.9, Forecast Windows=502023.11 | — | 1.43 | |
| RNNAverage Seq. Length=14.9, Forecast Windows=502023.11 | — | 0.95 | |
| TransformerAverage Seq. Length=14.9, Forecast Windows=502023.11 | — | 1.18 |