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GP CaKe: Effective brain connectivity with causal kernels

NeurIPS 2017 · Probabilistic and scientific modeling › Causal discovery · approach: Latent-variable causal estimation · 4 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use GP CaKe instead of VAR or ridge-regularized VAReffective connectivity kernel recovery · two-node and three-node simulated networksMSEHelped
Add ridge regularization to VAR (ablation)VAR · two-node and three-node simulated networksMSEHelped
Overestimate temporal smoothness (ablation)GP CaKe · simulated two-node networkkernel estimation accuracyHurt
Underestimate temporal smoothness (ablation)GP CaKe · simulated two-node networkkernel estimate varianceHurt
Overestimate the noise level (ablation)GP CaKe · simulated two-node networkkernel estimation accuracyHurt
Overestimate temporal localization (ablation)GP CaKe · simulated two-node networkduration of estimated causal influenceHurt
Use a fully disconnected estimate instead of GP CaKe or VAR at low connection strengtheffective connectivity kernel recovery · simulated networks with low connection strengthMSEHelped
Use GP CaKe or VAR instead of a fully disconnected estimateeffective connectivity kernel recovery · simulated networkscorrelationHelped

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