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Found 3 papers, 2 papers with code
MultiResFormer: Transformer with Adaptive Multi-Resolution Modeling for General Time Series Forecasting
Transformer-based models have greatly pushed the boundaries of time series forecasting recently.
DuETT: Dual Event Time Transformer for Electronic Health Records
Electronic health records (EHRs) recorded in hospital settings typically contain a wide range of numeric time series data that is characterized by high sparsity and irregular observations.
Temporal Dependencies in Feature Importance for Time Series Predictions
Time series data introduces two key challenges for explainability methods: firstly, observations of the same feature over subsequent time steps are not independent, and secondly, the same feature can have varying importance to model predictions over time.
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