Research map / Probabilistic and scientific modeling / Dynamical systems
Sparse Learning of Dynamical Systems in RKHS: An Operator-Theoretic Approach
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| sparsify dictionary via coherency threshold γ (sparse PF operator learning) versus full dataset | Duffing oscillator generator estimation (A⋆) · Duffing oscillator, Gaussian kernel | dictionary size |Dγ| | Helped |
| lower coherency threshold γ (sparser dictionary) | Quadruple-well SDE generator estimation · Quadruple-well dynamics, Gaussian kernel | dictionary size |Dγ| | Helped |
| estimating drift and diffusion from data instead of using known coefficients | Quadruple-well SDE generator estimation · Quadruple-well dynamics | dictionary size |Dγ| | Mixed |
| sparsification of dataset (sub-sampling with coherency) reducing dictionary size while approximating generator eigenfunctions | Ornstein-Uhlenbeck process · 1D OU process | dictionary size |Dγ| | Helped |
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