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 |
|---|---|---|
| Sentence | 72 | 7.64% |
| Sentiment Analysis | 41 | 4.35% |
| Named Entity Recognition (NER) | 38 | 4.03% |
| Language Modelling | 37 | 3.93% |
| NER | 34 | 3.61% |
| Text Classification | 29 | 3.08% |
| General Classification | 29 | 3.08% |
| Classification | 24 | 2.55% |
| Question Answering | 17 | 1.80% |
LSTM
