Results 1 to 10 of about 481,445 (263)
Some of the next articles are maybe not open access.
Composite Graph Neural Networks for Molecular Property Prediction
International Journal of Molecular SciencesPietro Bongini +2 more
exaly
Graph Theoretical Applications of Molecular Graphs
2017Yurttaş, Aysun +3 more
openaire +1 more source
Molecular Graph Eigenvectors for Molecular Coordinates.
Patrick W. Fowler +2 moreopenaire +1 more source
Compressed graph representation for scalable molecular graph generation [PDF]
AbstractRecently, deep learning has been successfully applied to molecular graph generation. Nevertheless, mitigating the computational complexity, which increases with the number of nodes in a graph, has been a major challenge. This has hindered the application of deep learning-based molecular graph generation to large molecules with many heavy atoms.
Youngchun Kwon +4 more
openaire +4 more sources
Group graph: a molecular graph representation with enhanced performance, efficiency and interpretability [PDF]
The exploration of chemical space holds promise for developing influential chemical entities. Molecular representations, which reflect features of molecular structure in silico, assist in navigating chemical space appropriately.
Piao-Yang Cao +5 more
doaj +2 more sources
The high-energy band in the photoelectron spectrum of alkanes and its dependence on molecular structure [PDF]
In the model for the ionization energies of the C2s-electrons in saturated hydrocarbons, put forward by Heilbronner et al., the energy levels are calculated as eigenvalues of the line graph of the hydrogen-filled molecular graph. It is now shown
Gutman Ivan +3 more
doaj +3 more sources
Degree-Based Graph Entropy in Structure–Property Modeling
Graph entropy plays an essential role in interpreting the structural information and complexity measure of a network. Let G be a graph of order n. Suppose dG(vi) is degree of the vertex vi for each i=1,2,…,n.
Sourav Mondal, Kinkar Chandra Das
doaj +1 more source

