Relative entropy minimizing noisy non-linear neural network to approximate stochastic processes

DOI10.1016/J.NEUNET.2014.04.002zbMath1347.60063arXiv1402.1613OpenAlexW1978148674WikidataQ51088425 ScholiaQ51088425MaRDI QIDQ889265

Gilles Wainrib, Camille Marini, Mathieu N. Galtier, Herbert Jaeger

Publication date: 6 November 2015

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1402.1613

zbMATH Keywords

relative entropyneural networksstochastic processesapproximationecho state networksEl Niño phenomenonlinear inverse modeling

Mathematics Subject Classification ID

Probabilistic models, generic numerical methods in probability and statistics (65C20) Neural networks for/in biological studies, artificial life and related topics (92B20) Other physical applications of random processes (60K40) Meteorology and atmospheric physics (86A10) Stochastic processes (60G99)

Related Items (2)

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Uses Software

• darch
• PRMLT

Cites Work

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