Research map / Probabilistic and scientific modeling / Dynamical systems
Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use TrSLDS instead of rSLDS | FitzHugh–Nagumo · FitzHugh–Nagumo test trajectories | multi-step prediction performance | Helped |
| Use TrSLDS instead of rSLDS | Tree Synthetic NASCAR · Tree Synthetic NASCAR | k-step R² | Helped |
| Use tree-structured rather than sequential stick-breaking | Tree Synthetic NASCAR · Tree Synthetic NASCAR | dynamics and partition recovery | Helped |
| Increase the tree depth to use finer-grained dynamics | TrSLDS · FitzHugh–Nagumo | dynamics resolution | Helped |
| Add child-level dynamics to the parent-level approximation | TrSLDS · Lorenz attractor | dynamics approximation | Helped |
| Use tree-structured dynamics to represent stimulus groups at different subtrees | TrSLDS · Macaque visual cortex neural data | separation of stimulus-dependent dynamics | Helped |
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