Research map / Probabilistic and scientific modeling / Causal discovery
GP CaKe: Effective brain connectivity with causal kernels
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use GP CaKe instead of VAR or ridge-regularized VAR | effective connectivity kernel recovery · two-node and three-node simulated networks | MSE | Helped |
| Add ridge regularization to VAR (ablation) | VAR · two-node and three-node simulated networks | MSE | Helped |
| Overestimate temporal smoothness (ablation) | GP CaKe · simulated two-node network | kernel estimation accuracy | Hurt |
| Underestimate temporal smoothness (ablation) | GP CaKe · simulated two-node network | kernel estimate variance | Hurt |
| Overestimate the noise level (ablation) | GP CaKe · simulated two-node network | kernel estimation accuracy | Hurt |
| Overestimate temporal localization (ablation) | GP CaKe · simulated two-node network | duration of estimated causal influence | Hurt |
| Use a fully disconnected estimate instead of GP CaKe or VAR at low connection strength | effective connectivity kernel recovery · simulated networks with low connection strength | MSE | Helped |
| Use GP CaKe or VAR instead of a fully disconnected estimate | effective connectivity kernel recovery · simulated networks | correlation | Helped |
Closest papers by meaning
- Generating Hypotheses of Dynamic Causal Graphs in Neuroscience: Leveraging Generative Factor Models of Observed Time Series (ICML 2025 · similarity 0.87)
- Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions (ICML 2024 · similarity 0.86)
- Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems (NeurIPS 2024 · similarity 0.85)
- Scalable inference of functional neural connectivity at submillisecond timescales (NeurIPS 2025 · similarity 0.85)
- Learning dynamic representations of the functional connectome in neurobiological networks (ICLR 2024 · similarity 0.84)
- Identifying Neural Dynamics Using Interventional State Space Models (ICML 2025 · similarity 0.84)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
