ArticleFrontiers in computational neuroscience2022
Dynamics and Information Import in Recurrent Neural Networks.
Article in Frontiers in computational neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Illuminating the black box of reservoir computing.Scientific reports · 2026Article
- Structural and dynamical strategies to prevent runaway excitation in reservoir computing.Frontiers in computational neuroscience · 2026Review
- Analysis of argument structure constructions in a deep recurrent language model.Frontiers in computational neuroscience · 2025Article
- Analysis of argument structure constructions in the large language model BERT.Frontiers in artificial intelligence · 2025Article
- The connectivity degree controls the difficulty in reservoir design of random boolean networks.Frontiers in computational neuroscience · 2024Article
- Neural network based formation of cognitive maps of semantic spaces and the putative emergence of abstract concepts.Scientific reports · 2023Article
- Excitatory/inhibitory balance emerges as a key factor for RBN performance, overriding attractor dynamics.Frontiers in computational neuroscience · 2023Article
- Classification at the accuracy limit: facing the problem of data ambiguity.Scientific reports · 2022Article
- Intrinsic Noise Improves Speech Recognition in a Computational Model of the Auditory Pathway.Frontiers in neuroscience · 2022Article
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Authors and funding
2 authors.
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Abstract
Recurrent neural networks (RNNs) are complex dynamical systems, capable of ongoing activity without any driving input. The long-term behavior of free-running RNNs, described by periodic, chaotic and fixed point attractors, is controlled by the statistics of the neural connection weights, such as the density
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Registered trials
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