The use of coarse-grained (CG) models is a popular approach to study complex
biomolecular systems. By reducing the number of degrees of freedom, a CG model can …

We utilize connections between molecular coarse-graining (CG) approaches and implicit
generative models in machine learning to describe a new framework for systematic …

Coarse-graining is a systematic reduction of the number of degrees of freedom used to
describe a system of interest. Coarse-graining can be thought of as a projection on the …

Bottom-up coarse-graining of polymers is commonly performed by matching structural order
parameters such as distribution of bond lengths, bending and dihedral angles, and pair …

Scientific documents contain tables that list important information in a concise fashion.
Structure and content extraction from tables embedded within PDF research documents is a …

The dual-potential approach promises coarse-grained (CG) models that accurately
reproduce both structural and energetic properties, while simultaneously providing …

Due to their computational efficiency, coarse-grained (CG) models are widely adopted for
modeling soft materials. As a consequence of averaging over atomistic details, the effective …

Tables present important information concisely in many scientific documents. Visual features
like mathematical symbols, equations, and spanning cells make structure and content …

We investigate the temperature-and density-dependence of effective pair potentials for 1-site
coarse-grained (CG) models of two industrial solvents, 1, 4-dioxane and tetrahydrofuran. We …

The systematic coarse graining of polymeric systems is a usual route in order to extend the
range of spatiotemporal scales and systems accessible to molecular simulations. Here, we …