arXiv (All)
open access
Overcoming the Curse of Dimensionality: Structural Connectivity Reconstruction via Pairwise Information Flow in Nonlinear Networks
Inferring structural connectivity from observed dynamics remains a fundamental open problem in complex systems, particularly for nonlinear networks where direct measurements are unavailable, and existing methodological approaches each incur characteristic limitations. Model-based methods require pri
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- When Dependence Disappears: Faithfulness and Effective Independence in Nonlinear Dynamical Systems#690837
- Microfluidic platforms for probing spontaneous functional recovery in hierarchically modular neuronal networks.#465283
- Network analysis of surface deformation reveals trunk modularity and synchronization during gait.#610482
- Structural Connectome Analysis using a Graph-based Deep Model for Prediction of Non-Imaging Variables#169079
- Structural connectome analysis using a graph-based deep model for prediction of non-imaging variables#1250332
Record · ID 1328305
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive