Deep Tabular Learning
Bidirectional LSTM
A Bidirectional LSTM, or biLSTM, is a sequence processing model that consists of two LSTMs: one taking the input in a forward direction, and the other in a backwards direction. BiLSTMs effectively increase the amount of information available to the network, improving the context available to the algorithm (e.g. knowing what words immediately follow and precede a word in a sentence).
Image Source: Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks, Cornegruta et al
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Language Modelling | 41 | 4.82% |
| Sentiment Analysis | 40 | 4.71% |
| Named Entity Recognition (NER) | 36 | 4.24% |
| General Classification | 33 | 3.88% |
| NER | 32 | 3.76% |
| Text Classification | 29 | 3.41% |
| Classification | 23 | 2.71% |
| Question Answering | 20 | 2.35% |
| Dependency Parsing | 18 | 2.12% |
LSTM
