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Reconstruction of Enhanced Causal Omnidirectional Network (RECON)

Praveen Niranda · Peter T. McKenney · Guifang Fu首次提交 2026-07-23 · 修订 2026-07-23 · v1arXiv预印本

增强因果全向网络重建：RECONAI 解读

Learning a dynamical system and reconstructing the underlying regulatory network from $p$ discretely observed state trajectories remain challenging problems. Existing approaches often produced a large number of spurious edges and suffered from several methodological limitations. We propose a new approach, Reconstruction of Enhanced Causal Omnidirectional Network (RECON), that leverages an integral-based additive nonparametric ODE model to reconstruct regulatory networks from…Learning a dynamical system and reconstructing the underlying regulatory network from $p$ discretely observed state trajectories remain challenging problems. Existing approaches often produced a large number of spurious edges and suffered from several methodological limitations. We propose a new approach, Reconstruction of Enhanced Causal Omnidirectional Network (RECON), that leverages an integral-based additive nonparametric ODE model to reconstruct regulatory networks from…

因果推断空间与网络面板数据

关联记录被引 0 次 ↗OpenAlex · 核验 2026-10-01

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