RecurrentLayers
LuxRecurrentLayers.jl extends Lux.jl recurrent layers offering by providing implementations of additional recurrent layers not available in base deep learning libraries.
Features
The package offers multiple layers for Lux.jl. Currently there are 25+ cells implemented, together with multiple higher level implementations:
| Short name | Publication venue | Official implementation |
|---|---|---|
| AntisymmetricRNN/GatedAntisymmetricRNN | ICLR 2019 | – |
| ATR | EMNLP 2018 | bzhangGo/ATR |
| BR/BRC | PLOS ONE 2021 | nvecoven/BRC |
| CFN | ICLR 2017 | – |
| coRNN | ICLR 2021 | tk-rusch/coRNN |
| FastRNN/FastGRNN | NeurIPS 2018 | Microsoft/EdgeML |
| IndRNN | CVPR 2018 | Sunnydreamrain/IndRNNTheanoLasagne |
| JANET | arXiv 2018 | JosvanderWesthuizen/janet |
| LEM | ICLR 2022 | tk-rusch/LEM |
| LiGRU | IEEE Transactions on Emerging Topics in Computing 2018 | mravanelli/theano-kaldi-rnn |
| LightRU | MDPI Electronics 2023 | – |
| MinimalRNN | NeurIPS 2017 | – |
| MultiplicativeLSTM | Workshop ICLR 2017 | benkrause/mLSTM |
| MGU | International Journal of Automation and Computing 2016 | – |
| MUT1/MUT2/MUT3 | ICML 2015 | – |
| NAS | arXiv 2016 | – |
| OriginalLSTM | Neural Computation 1997 | - |
| PeepholeLSTM | JMLR 2002 | – |
| RAN | arXiv 2017 | kentonl/ran |
| RHN | ICML 2017 | jzilly/RecurrentHighwayNetworks |
| SCRN | ICLR 2015 | facebookarchive/SCRNNs |
| SGRN | IET 2018 | – |
| STAR | IEEE Transactions on Pattern Analysis and Machine Intelligence 2022 | 0zgur0/STAckable-Recurrent-network |
| Typed RNN / GRU / LSTM | ICML 2016 | – |
| UGRNN | ICLR 2017 | - |
| UnICORNN | ICML 2021 | tk-rusch/unicornn |
| WMCLSTM | Neural Networks 2021 | – |
Installation
You can install LuxRecurrentLayers using either of:
using Pkg
Pkg.add("LuxRecurrentLayers")julia> ]
pkg> add LuxRecurrentLayers