Recurrent Neural Networks
Efficient Recurrent Unit
Introduced by Mehta et al. in ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural NetworkAn Efficient Recurrent Unit (ERU) extends LSTM-based language models by replacing linear transforms for processing the input vector with the EESP unit inside the LSTM cell.
Source: ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| document understanding | 1 | 8.33% |
| 3D visual grounding | 1 | 8.33% |
| Visual Grounding | 1 | 8.33% |
| General Classification | 1 | 8.33% |
| Image Classification | 1 | 8.33% |
| Language Modeling | 1 | 8.33% |
| Language Modelling | 1 | 8.33% |
| Object | 1 | 8.33% |
| Object Detection | 1 | 8.33% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
Dropout
|
Regularization | |
EESP
|
Image Model Blocks | |
LSTM
|
Recurrent Neural Networks |
