Who Cited It

A Learning Algorithm for Continually Running Fully Recurrent Neural Networks

1989 · Neural Computation · 4,490 citations · 14 from inside this corpus

Ronald J. Williams, David Zipser low

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.

A Learning Algorithm for Continually Running Fully Recurrent Neural Networks (1989)A Learning Algorithm for Cont…Learning Internal Representations by Error Propagation (1985)Learning Internal Representat…Deep learning in neural networks: An overview (2014)Deep learning in neural netwo…Learning long-term dependencies with gradient descent is difficult (1994)Learning long-term dependenci…Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) network (2020)Fundamentals of Recurrent Neu…Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communi… (2004)Harnessing Nonlinearity: Pred…Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (2019)Exploring the Limits of Trans…Deep learning for healthcare: review, opportunities and challenges (2017)Deep learning for healthcare:…Reservoir computing approaches to recurrent neural network training (2009)Reservoir computing approache…Neuro-fuzzy modeling and control (1995)Neuro-fuzzy modeling and cont…30 years of adaptive neural networks: perceptron, Madaline, and backpropagation (1990)30 years of adaptive neural n…Recent advances in physical reservoir computing: A review (2019)Recent advances in physical r…Deep Learning for Health Informatics (2016)Deep Learning for Health Info…Neural networks for control systems—A survey (1992)Neural networks for control s…[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)][No title in the source recor…Self-improving reactive agents based on reinforcement learning, planning and teaching (1992)Self-improving reactive agent…
15 of 15 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
Learning Internal Representations by Error Propagation198516,273

What cites it, inside the corpus

PaperYearCited
Deep learning in neural networks: An overview201418,236
Learning long-term dependencies with gradient descent is difficult19948,610
Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) network20205,639
Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communi…20043,862
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer20193,698
Deep learning for healthcare: review, opportunities and challenges20173,115
Reservoir computing approaches to recurrent neural network training20092,992
Neuro-fuzzy modeling and control19952,332
30 years of adaptive neural networks: perceptron, Madaline, and backpropagation19902,244
Recent advances in physical reservoir computing: A review20192,125
Deep Learning for Health Informatics20162,015
Neural networks for control systems—A survey19921,871
[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)]1,853
Self-improving reactive agents based on reinforcement learning, planning and teaching19921,656

Links

DOI · OpenAlex record

Topics

Neural Networks and ApplicationsComputer Science
Neural Networks and Reservoir ComputingComputer Science
Cognitive Science and Education ResearchNeuroscience

Is this record sound?

complete

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

  • supports2 author record(s) attached.
  • supports14 reference(s) recorded.
  • supportsThe DOI's year agrees with the publication year.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:44+00:00.

sha256 648f8491aaceaa34…