Trainable dissipative oscillator networks exhibit a trilemma in which damping governs memory horizon, gradient stability, and Lyapunov exponent, with learned substrates outperforming frozen ones only at short horizons before the advantage closes near eleven steps.
Japanese Journal of Applied Physics, 59(6):060501, 2020.https://arxiv.org/abs/2005.00992
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Between Amnesia and Chaos: A Memory Stability Expressivity Trilemma for Trainable Dissipative Oscillator Networks
Trainable dissipative oscillator networks exhibit a trilemma in which damping governs memory horizon, gradient stability, and Lyapunov exponent, with learned substrates outperforming frozen ones only at short horizons before the advantage closes near eleven steps.