applicable models
recurrent
Techniques for RNNs, LSTMs, and GRUs
3 techniques
| Goals | Models | Data Types | Description | |||
|---|---|---|---|---|---|---|
| Contextual Decomposition | Algorithmic | Architecture/neural Networks/recurrent Requirements/white Box +1 | Text | Contextual Decomposition explains why an LSTM, a neural network that reads text one word at a time, made a particular... | ||
| Attention Weight Analysis | Algorithmic | Architecture/neural Networks/recurrent Architecture/neural Networks/transformer +2 | Image Text | Attention weight analysis reads the weights an attention-based neural network assigns to the parts of its input, to see... | ||
| TimeSHAP | Algorithmic | Architecture/neural Networks/recurrent Requirements/black Box | Time-series | TimeSHAP explains one prediction of a model that reads a sequence of events, such as a recurrent neural network that... |
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