Cargando…
One for all: Universal material model based on minimal state-space neural networks
Computational models describing the mechanical behavior of materials are indispensable when optimizing the stiffness and strength of structures. The use of state-of-the-art models is often limited in engineering practice due to their mathematical complexity, with each material class requiring its ow...
Autores principales: | Bonatti, Colin, Mohr, Dirk |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8221615/ https://www.ncbi.nlm.nih.gov/pubmed/34162539 http://dx.doi.org/10.1126/sciadv.abf3658 |
Ejemplares similares
-
Avalanches in Self-Organized Critical Neural Networks: A Minimal Model for the Neural SOC Universality Class
por: Rybarsch, Matthias, et al.
Publicado: (2014) -
A Universal 3D Voxel Descriptor for Solid-State Material Informatics with Deep Convolutional Neural Networks
por: Kajita, Seiji, et al.
Publicado: (2017) -
Upper-Bound Energy
Minimization to Search for Stable
Functional Materials with Graph Neural Networks
por: Law, Jeffrey N., et al.
Publicado: (2022) -
Switching state-space modeling of neural signal dynamics
por: He, Mingjian, et al.
Publicado: (2023) -
Networking all-in-one for dummies
por: Lowe, Doug
Publicado: (2010)