Model of time-dependent geometric graph for dynamical Casimir effect
Sign Up to like & getrecommendations! Published in 2020 at "Indian Journal of Physics"
DOI: 10.1007/s12648-020-01866-5
Abstract: Geometric graph model is suggested for the dynamical Casimir effect. The wave equation is considered at the graph edges and the Kirchhoff condition at the internal vertex. It is assumed that the edge lengths depend… read more here.
Keywords: dynamical casimir; model; geometric graph; casimir effect ... See more keywords
End-to-End Modeling of Reaction Field Energy Using Data-Driven Geometric Graph Neural Networks.
Sign Up to like & getrecommendations! Published in 2025 at "Journal of chemical theory and computation"
DOI: 10.1021/acs.jctc.5c01193
Abstract: Electrostatic interactions are fundamental to the structure, dynamics, and function of biomolecules, with broad applications in protein-ligand binding, enzymatic catalysis, and nucleic acid regulation. The Poisson-Boltzmann (PB) equation provides a physically grounded framework for modeling… read more here.
Keywords: driven geometric; end; energy; end end ... See more keywords
Pretrainable geometric graph neural network for antibody affinity maturation
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DOI: 10.1038/s41467-024-51563-8
Abstract: Increasing the binding affinity of an antibody to its target antigen is a crucial task in antibody therapeutics development. This paper presents a pretrainable geometric graph neural network, GearBind, and explores its potential in in… read more here.
Keywords: antibody; graph neural; affinity; pretrainable geometric ... See more keywords
Collaborative Navigation of Multiple Autonomous Mobile Robots via Geometric Graph Neural Network
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Industrial Electronics"
DOI: 10.1109/tie.2025.3574516
Abstract: Multiple mobile robots play a crucial role in spatially distributed tasks. In unknown and nonrepetitive scenarios, reconstructing a global map is time-consuming and often unnecessary. Hence, research has focused on real-time collaborative planning without relying… read more here.
Keywords: navigation; mobile robots; graph neural; neural network ... See more keywords
Generalization of Geometric Graph Neural Networks With Lipschitz Loss Functions
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2025.3553378
Abstract: In this paper, we study the generalization capabilities of geometric graph neural networks (GNNs). We consider GNNs over a geometric graph constructed from a finite set of randomly sampled points over an embedded manifold with… read more here.
Keywords: geometric graph; graph neural; sampled points; generalization ... See more keywords