Who Cited It

On the difficulty of training Recurrent Neural Networks

2012 · arXiv (Cornell University) · 3,801 citations · 14 from inside this corpus

Razvan Pascanu, Tomáš Mikolov, Yoshua Bengio

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

On the difficulty of training Recurrent Neural Networks (2012)On the difficulty of training…Long Short-Term Memory (1997)Long Short-Term MemoryLearning representations by back-propagating errors (1986)Learning representations by b…Adaptive Subgradient Methods for Online Learning and Stochastic Optimization (2010)Adaptive Subgradient Methods …Learning long-term dependencies with gradient descent is difficult (1994)Learning long-term dependenci…Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communi… (2004)Harnessing Nonlinearity: Pred…Reservoir computing approaches to recurrent neural network training (2009)Reservoir computing approache…Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh… (2015)Batch Normalization: Accelera…Deep learning in neural networks: An overview (2014)Deep learning in neural netwo…Sequence to Sequence Learning with Neural Networks (2014)Sequence to Sequence Learning…Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning (2017)Inception-v4, Inception-ResNe…[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)][No title in the source recor…Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) network (2020)Fundamentals of Recurrent Neu…Bootstrap your own latent: A new approach to self-supervised Learning (2020)Bootstrap your own latent: A …Character-level Convolutional Networks for Text Classification (2015)Character-level Convolutional…End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF (2016)End-to-end Sequence Labeling …Conditional Random Fields as Recurrent Neural Networks (2015)Conditional Random Fields as …Deep Learning: Methods and Applications (2014)Deep Learning: Methods and Ap…Convolutional, Long Short-Term Memory, fully connected Deep Neural Networks (2015)Convolutional, Long Short-Ter…An Empirical Exploration of Recurrent Network Architectures (2015)An Empirical Exploration of R…End-to-End Training of Deep Visuomotor Policies (2015)End-to-End Training of Deep V…
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What this paper cites, inside the corpus

PaperYearCited
Long Short-Term Memory1997101,359
Learning representations by back-propagating errors198631,688
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization20108,621
Learning long-term dependencies with gradient descent is difficult19948,610
Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communi…20043,862
Reservoir computing approaches to recurrent neural network training20092,992

What cites it, inside the corpus

PaperYearCited
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…201524,404
Deep learning in neural networks: An overview201418,236
Sequence to Sequence Learning with Neural Networks201413,351
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning201712,734
[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)]7,291
Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) network20205,639
Bootstrap your own latent: A new approach to self-supervised Learning20203,447
Character-level Convolutional Networks for Text Classification20153,280
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF20162,595
Conditional Random Fields as Recurrent Neural Networks20152,437
Deep Learning: Methods and Applications20141,801
Convolutional, Long Short-Term Memory, fully connected Deep Neural Networks20151,646
An Empirical Exploration of Recurrent Network Architectures20151,406
End-to-End Training of Deep Visuomotor Policies20151,400

Links

DOI · Open access copy · OpenAlex record

Topics

Neural Networks and ApplicationsComputer Science
Model Reduction and Neural NetworksPhysics and Astronomy
Domain Adaptation and Few-Shot LearningComputer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports3 author record(s) attached.
  • supports23 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:46+00:00.

sha256 bba2969b3567609a…