Horizon-constrained Rashomon sets contract exponentially with lead time at a rate given by the maximum Lyapunov exponent, with Lyapunov-weighted metrics and decision-aligned selection improving downstream utility in chaotic forecasting.
We employ the Rosenstein algorithm, a widely-adopted method designed specifically for noisy, finite- length time series typical of empirical chaotic systems
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Horizon-Constrained Rashomon Sets for Chaotic Forecasting
Horizon-constrained Rashomon sets contract exponentially with lead time at a rate given by the maximum Lyapunov exponent, with Lyapunov-weighted metrics and decision-aligned selection improving downstream utility in chaotic forecasting.