Who Cited It

Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication

2004 · Science · 3,862 citations · 9 from inside this corpus

Herbert Jaeger, Harald Haas

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.

Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communi… (2004)Harnessing Nonlinearity: Pred…Backpropagation through time: what it does and how to do it (1990)Backpropagation through time:…A Learning Algorithm for Continually Running Fully Recurrent Neural Networks (1989)A Learning Algorithm for Cont…Real-Time Computing Without Stable States: A New Framework for Neural Computation Based o… (2002)Real-Time Computing Without S…'Neural-gas' network for vector quantization and its application to time-series prediction (1993)'Neural-gas' network for vect…Deep learning in neural networks: An overview (2014)Deep learning in neural netwo…On the difficulty of training Recurrent Neural Networks (2012)On the difficulty of training…On the importance of initialization and momentum in deep learning (2013)On the importance of initiali…Reservoir computing approaches to recurrent neural network training (2009)Reservoir computing approache…Recent advances in physical reservoir computing: A review (2019)Recent advances in physical r…Information processing using a single dynamical node as complex system (2011)Information processing using …Quantum circuit learning (2018)Quantum circuit learningAn Empirical Exploration of Recurrent Network Architectures (2015)An Empirical Exploration of R…A Survey on Deep Learning (2018)A Survey on Deep Learning
13 of 13 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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Citation edge evidence

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What this paper cites, inside the corpus

PaperYearCited
Backpropagation through time: what it does and how to do it19904,971
A Learning Algorithm for Continually Running Fully Recurrent Neural Networks19894,490
Real-Time Computing Without Stable States: A New Framework for Neural Computation Based o…20024,117
'Neural-gas' network for vector quantization and its application to time-series prediction19931,448

What cites it, inside the corpus

PaperYearCited
Deep learning in neural networks: An overview201418,236
On the difficulty of training Recurrent Neural Networks20123,801
On the importance of initialization and momentum in deep learning20133,523
Reservoir computing approaches to recurrent neural network training20092,992
Recent advances in physical reservoir computing: A review20192,125
Information processing using a single dynamical node as complex system20111,720
Quantum circuit learning20181,667
An Empirical Exploration of Recurrent Network Architectures20151,406
A Survey on Deep Learning20181,398

Links

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Topics

Neural Networks and Reservoir ComputingComputer Science
Advanced Memory and Neural ComputingEngineering
Neural Networks and ApplicationsComputer Science

Is this record sound?

complete

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

  • supports2 author record(s) attached.
  • supports18 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…