Results 41 to 50 of about 2,382 (198)

FIRE‐GNN: Force‐Informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties

Advanced Intelligent Discovery, EarlyView.
This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu, Claire Schlesinger, Karan Mudaliar, Jordan Leung, Robin Walters, Peter Schindler   +5 more
wiley   +1 more source

On eternal domination and Vizing-type inequalities

AKCE International Journal of Graphs and Combinatorics, 2020
We show sharp Vizing-type inequalities for eternal domination. Namely, we prove that for any graphs G and H, where is the eternal domination function, α is the independence number, and is the strong product of graphs.
Keith Driscoll, William F. Klostermeyer, Elliot Krop, Colton Magnant, Patrick Taylor   +4 more
doaj   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

Interval-Valued Fuzzy Soft Graphs

Topological Algebra and its Applications, 2017
In this paper, we combine concepts of interval-valued fuzzy soft sets and graph theory. Then we introduce notations of interval-valued fuzzy soft graphs and complete interval-valued fuzzy soft graphs.
Zihni Onur, Çelik Yıldıray, Kara Güven   +2 more
doaj   +1 more source

Adjacent vertex distinguishing acyclic edge coloring of the Cartesian product of graphs [PDF]

Transactions on Combinatorics, 2017
‎Let $G$ be a graph and $chi^{prime}_{aa}(G)$ denotes the minimum number of colors required for an‎ ‎acyclic edge coloring of $G$ in which no two adjacent vertices are incident to edges colored with the same set of colors‎. ‎We prove a general bound for $
Fatemeh Sadat Mousavi, Massomeh Noori
doaj   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

On the δ-chromatic numbers of the Cartesian products of graphs

Open Mathematics
In this work, we study the δ\delta -chromatic number of a graph, which is the chromatic number of the δ\delta -complement of a graph. We give a structure of the δ\delta -complements and sharp bounds on the δ\delta -chromatic numbers of the Cartesian ...
Tangjai Wipawee, Pho-on Witsarut, Vichitkunakorn Panupong   +2 more
doaj   +1 more source

Weighted Szeged indices of some graph operations [PDF]

Transactions on Combinatorics, 2016
In this paper, the weighted Szeged indices of Cartesian product and Corona product of twoconnected graphs are obtained. Using the results obtained here, the weighted Szeged indices ofthe hypercube of dimension n, Hamming graph, C4 nanotubes, nanotorus ...
Kannan Pattabiraman, P. Kandan
doaj  

Complexity of Products of Some Complete and Complete Bipartite Graphs

Journal of Applied Mathematics, 2013
The number of spanning trees in graphs (networks) is an important invariant; it is also an important measure of reliability of a network. In this paper, we derive simple formulas of the complexity, number of spanning trees, of products of some complete ...
S. N. Daoud
doaj   +1 more source

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

Advanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi, Yu Kumagai, Arata Takamatsu, Fumiyasu Oba   +3 more
wiley   +1 more source