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20032023
most citedIntegrating Machine Learning and Multiscale Modeling: Perspectives, Challenges, and Opportunities in the Biological, Biomedical, and Behavioral Sciences

645 citations · 2.1k across the 59 of their papers we have counts for

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Showing 2019Show all

9 papers · 1 filter

cond-mat.mtrl-sci2019★ 4 cited

Modeling strength and failure variability due to porosity in additively manufactured metals

M. Khalil, G. H. Teichert, C. Alleman +4

To model and quantify the variability in plasticity and failure of additively manufactured metals due to imperfections in their microstructure, we have developed uncertainty quanti…

math.NA2019★ 12 cited

Second Order Threshold Dynamics Schemes for Two Phase Motion by Mean Curvature

Alexander Zaitzeff, Selim Esedoglu, Krishna Garikipati

The threshold dynamics algorithm of Merriman, Bence, and Osher is only first order accurate in the two-phase setting. Its accuracy degrades further to half order in the multi-phase…

physics.bio-ph2019

Multiscale modeling meets machine learning: What can we learn?

Grace C. Y. Peng, Mark Alber, Adrian Buganza Tepole +9

Machine learning is increasingly recognized as a promising technology in the biological, biomedical, and behavioral sciences. There can be no argument that this technique is incred…

q-bio.QM2019★ 645 cited

Integrating Machine Learning and Multiscale Modeling: Perspectives, Challenges, and Opportunities in the Biological, Biomedical, and Behavioral Sciences

Mark Alber, Adrian Buganza Tepole, William Cannon +8

Fueled by breakthrough technology developments, the biological, biomedical, and behavioral sciences are now collecting more data than ever before. There is a critical need for time…

math.NA2019

Variational Extrapolation of Implicit Schemes for General Gradient Flows

Alexander Zaitzeff, Selim Esedoglu, Krishna Garikipati

We introduce a class of unconditionally energy stable, high order accurate schemes for gradient flows in a very general setting. The new schemes are a high order analogue of the mi…

physics.bio-ph2019★ 36 cited

A mechanical model reveals that non-axisymmetric buckling lowers the energy barrier associated with membrane neck constriction

Ritvik Vasan, Shiva Rudraraju, Matthew Akamatsu +2

Membrane neck formation is essential for scission, which, as recent experiments on tubules have demonstrated, can be location dependent. The diversity of biological machinery that…