AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A committor-based method that promotes frequent transitions between the metastable states of the system and allows extensive sampling of the process transition state ensemble and highlights the advantages of a graph-based approach in describing the role of solvent molecules in systems, such as ion pair dissociation or ligand binding.
Recent developments in ML potentials, ML collective variables, and committor-based sampling are presented as innovative methods that have been able to address some of the current challenges in accuracy, sampling efficiency, and the identification of low-dimensional representations of reaction coordinates.
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