Spatiotemporal Connectionist Networks: A Taxonomy and Review

DOI10.1162/089976601300014538zbMath0973.68200OpenAlexW2136451213WikidataQ128253236 ScholiaQ128253236MaRDI QIDQ2708443

Stefan C. Kremer

Publication date: 17 April 2001

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

Full work available at URL: https://doi.org/10.1162/089976601300014538

zbMATH Keywords

training algorithmsconnectionist network architectures

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (9)

Architectural Bias in Recurrent Neural Networks: Fractal Analysis ⋮ A Taxonomy for Spatiotemporal Connectionist Networks Revisited: The Unsupervised Case ⋮ Nonmonotone BFGS-trained recurrent neural networks for temporal sequence processing ⋮ Schema-based learning of adaptable and flexible prey-catching in anurans. II: Learning after lesioning ⋮ Recursive self-organizing network models ⋮ Rule Extraction from Recurrent Neural Networks: ATaxonomy and Review ⋮ Universal Approximation Capability of Cascade Correlation for Structures ⋮ Stack-like and queue-like dynamics in recurrent neural networks ⋮ The Crystallizing Substochastic Sequential Machine Extractor: CrySSMEx

Uses Software

• LSTM

Cites Work

• A recurrent network for modeling noisy temporal sequences
• Non-linear system identification using neural networks
• Constructing deterministic finite-state automata in recurrent neural networks

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