Statements (27)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:model
|
| gptkbp:arXivID |
1912.09363
|
| gptkbp:citation |
2020
Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting |
| gptkbp:designedFor |
multi-horizon time series forecasting
|
| gptkbp:developedBy |
gptkb:Bryan_Lim
Nicolas Loeff Sercan Ö. Arik Tomas Pfister |
| gptkbp:hasFeature |
quantile regression
scalable to large datasets handling missing data handling static and time-varying covariates interpretable attention weights multi-step forecasting |
| https://www.w3.org/2000/01/rdf-schema#label |
Temporal Fusion Transformer
|
| gptkbp:implementedIn |
gptkb:PyTorch
|
| gptkbp:input |
multivariate time series
|
| gptkbp:openSource |
yes
|
| gptkbp:output |
future time series predictions
|
| gptkbp:publishedIn |
gptkb:NeurIPS_2020
|
| gptkbp:uses |
attention mechanism
gating mechanisms interpretable outputs variable selection networks |
| gptkbp:bfsParent |
gptkb:PyTorch_Forecasting
|
| gptkbp:bfsLayer |
6
|