Discovering cognitive strategies with tiny recurrent neural networks. [PDF]
Ji-An L, Benna MK, Mattar MG.
europepmc +1 more source
Sequential temporal anticipation characterized by neural power modulation and in recurrent neural networks. [PDF]
Teng X, Zhang RY.
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Modeling chaotic diabetes systems using fully recurrent neural networks enhanced by fractional-order learning. [PDF]
Mostafa E, Mahmoud TA, El-Brawany MA.
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Population coding and self-organized ring attractors in recurrent neural networks for continuous variable integration. [PDF]
Kononov R +3 more
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Recurrent neural networks as neuro-computational models of human speech recognition. [PDF]
Brodbeck C, Hannagan T, Magnuson JS.
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Training Recurrent Neural Networks for BrdU Detection with Oxford Nanopore Sequencing: Guidance and Lessons Learned. [PDF]
Liu H, Flavahan W, Zhu LJ.
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Structure of activity in multiregion recurrent neural networks. [PDF]
Clark DG, Beiran M.
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Addressing the Problem of Lysine Glycation Prediction in Proteins via Recurrent Neural Networks. [PDF]
Que-Salinas U +5 more
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Diverse and flexible behavioral strategies arise in recurrent neural networks trained on multisensory decision making. [PDF]
Wierda TS +3 more
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