ArticlePhysical review. X
Theory of Gating in Recurrent Neural Networks.
Article in Physical review. X. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
23 citing papers in PubMed.
- Article
- Neural timescales from a computational perspective.Nature neuroscience · 2026Review
- Article
- Neural mechanisms of flexible perceptual inference.PLoS computational biology · 2025Article
- Slow Transition to Low-Dimensional Chaos in Heavy-Tailed Recurrent Neural Networks.bioRxiv : the preprint server for biology · 2025Article
- Article
- Disinhibition of a recurrent attractor gates a persistent goal signal for navigation.bioRxiv : the preprint server for biology · 2025Article
- Dynamical mean-field theory for a highly heterogeneous neural population with graded persistent activity of the entorhinal cortex.PLoS computational biology · 2025Article
- Balanced state of networks of winner-take-all units.PLoS computational biology · 2025Article
- Inferring neural population codes forProceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- Modeling of whole brain sleep electroencephalogram using deep oscillatory neural network.Frontiers in neuroinformatics · 2025Article
- Neural networks with optimized single-neuron adaptation uncover biologically plausible regularization.PLoS computational biology · 2024Article
- SERT-StructNet: Protein secondary structure prediction method based on multi-factor hybrid deep model.Computational and structural biotechnology journal · 2024Article
- Abrupt and spontaneous strategy switches emerge in simple regularised neural networks.PLoS computational biology · 2024Article
- Chaotic neural dynamics facilitate probabilistic computations through sampling.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Complexity-calibrated benchmarks for machine learning reveal when prediction algorithms succeed and mislead.Scientific reports · 2024Article
- Brain mechanism of foraging: Reward-dependent synaptic plasticity versus neural integration of values.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Inferring neural dynamics of memory during naturalistic social communication.bioRxiv : the preprint server for biology · 2024Article
- Neural heterogeneity controls computations in spiking neural networks.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Recurrent neural networks (RNNs) are powerful dynamical models, widely used in machine learning (ML) and neuroscience. Prior theoretical work has focused on RNNs with additive interactions. However gating i.e., multiplicative interactions are ubiquitous in real neurons and also
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.