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1912.11213
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Optimal short-term memory before the edge of chaos in driven random recurrent networks
24 December 2019
T. Haruna
Kohei Nakajima
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ArXiv (abs)
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Papers citing
"Optimal short-term memory before the edge of chaos in driven random recurrent networks"
7 / 7 papers shown
Title
Neuronal correlations shape the scaling behavior of memory capacity and nonlinear computational capability of recurrent neural networks
Shotaro Takasu
Toshio Aoyagi
102
0
0
28 Apr 2025
Attractor-merging Crises and Intermittency in Reservoir Computing
Tempei Kabayama
Motomasa Komuro
Yasuo Kuniyoshi
Kazuyuki Aihara
Kohei Nakajima
75
0
0
17 Apr 2025
How noise affects memory in linear recurrent networks
JingChuan Guan
T. Kubota
Yasuo Kuniyoshi
Kohei Nakajima
22
0
0
05 Sep 2024
Quantifying and maximizing the information flux in recurrent neural networks
C. Metzner
Marius E. Yamakou
Dennis Voelkl
A. Schilling
P. Krauss
70
7
0
30 Jan 2023
Edge of chaos as a guiding principle for modern neural network training
Lin Zhang
Ling Feng
Kan Chen
C. Lai
117
10
0
20 Jul 2021
Learning Temporal Quantum Tomography
Quoc Hoan Tran
Kohei Nakajima
48
29
0
25 Mar 2021
Physical reservoir computing -- An introductory perspective
Kohei Nakajima
86
313
0
03 May 2020
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