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Identifiability of Latent Space Network Models on Anisotropic Thurston Geometries
США и Запад ·
arXiv:2609.09236v1 Announce Type: new Abstract: A latent space network model places the nodes in a metric space and lets the probability of a tie decrease with distance. In a space of constant curvature, pairwise distances determine the positions up to an isometry.
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Identifiability of Latent Space Network Models on Anisotropic Thurston Geometries
arXiv:2609.35819v1 Announce Type: new Abstract: In this paper, we explore using generative agent-based models for a classical ABM application: testing how individual-level behavioral rules produce collective phenomena.
arXiv:2410.09166v2 Announce Type: replace Abstract: Battery energy storage systems (BESS) play an increasingly vital role in integrating renewable generation into power grids due to their ability to dynamically balance supply.
arXiv:2501.05815v2 Announce Type: replace Abstract: This paper introduces a novel nonlinear model predictive control (NMPC) framework that incorporates a lifting technique to enhance control performance for nonlinear systems.