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  • Models

Models#

This page lists all recurrent models available in torchrecurrent, with references and official implementations where available.

  • Clicking on the model name will bring you to its API documentation.

  • Clicking on the publication venue will bring you to the arXiv paper (or directly to the publication).

  • The last column provides links to any official implementations if they exist.

Model

Publication

Official implementation

AntisymmetricRNN

ICLR 2019

–

ATR

EMNLP 2018

bzhangGo/ATR

BR

PLOS ONE 2021

nvecoven/BRC

CFN

ICLR 2017

–

coRNN

ICLR 2021

tk-rusch/coRNN

FastGRNN

NeurIPS 2018

Microsoft/EdgeML

FastRNN

NeurIPS 2018

Microsoft/EdgeML

GatedAntisymmetricRNN

ICLR 2019

–

IndRNN

CVPR 2018

Sunnydreamrain/IndRNN_Theano_Lasagne

JANET

arXiv 2018

JosvanderWesthuizen/janet

LEM

ICLR 2022

tk-rusch/LEM

LiGRU

IEEE TETC 2018

mravanelli/theano-kaldi-rnn

LightRU

MDPI Electronics 2023

–

MGU

IJAC 2016

–

MultiplicativeLSTM

Workshop ICLR 2017

benkrause/mLSTM

MUT1

ICML 2015

–

MUT2

ICML 2015

–

MUT3

ICML 2015

–

NAS

arXiv 2016

tensorflow_addons/rnn

NBR

PLOS ONE 2021

nvecoven/BRC

OriginalLSTM

Neural Computation 1997

–

PeepholeLSTM

JMLR 2002

–

RAN

arXiv 2017

kentonl/ran

SCRN

ICLR 2015

facebookarchive/SCRNNs

SGRN

IET 2018

–

STAR

TPAMI 2022

0zgur0/STAckable-Recurrent-network

UGRNN

ICLR 2017

–

UnICORNN

ICML 2021

tk-rusch/unicornn

WMCLSTM

Neural Networks 2021

–

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