A proposed meta-learning framework trains stochastic dynamical systems by evolutionary selection over mutant trajectories, reducing the tuning burden to two timescales, µ and τ.
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Greedy dynamical meta-learning
A proposed meta-learning framework trains stochastic dynamical systems by evolutionary selection over mutant trajectories, reducing the tuning burden to two timescales, µ and τ.