Results 171 to 180 of about 12,423 (291)
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Topological data analysis and topological deep learning beyond persistent homology: a review. [PDF]
Su Z +7 more
europepmc +1 more source
Comparing the Latent Features of Universal Machine‐Learning Interatomic Potentials
This study quantitatively assesses how universal machine‐learning interatomic potentials encode the chemical space into latent features, showing unique model‐specific representations with high cross‐model reconstruction errors. It explores how training datasets, protocols, and targets affect these encodings.
Sofiia Chorna +5 more
wiley +1 more source
Estimating the Hydrogen Bond Strength by Machine Learning Approaches. [PDF]
Samangani N, Zahn S.
europepmc +1 more source
Commuting planar polynomial vector fields for conservative Newton systems [PDF]
Joel Nagloo +2 more
openalex +1 more source
Applications of representation theory and of explicit units to Leopoldt's conjecture. [PDF]
Ferri F, Johnston H.
europepmc +1 more source
Leveraging Climate Data Through Intelligent Systems for the Prediction of Arbovirus Transmission by Aedes aegypti. [PDF]
Lima CL +8 more
europepmc +1 more source
Effects of modified woods saxon potential on quantum dynamics of spin 0 scalar particle in a cosmic string spacetime. [PDF]
Ahmed F, Bouzenada A.
europepmc +1 more source

