Showing results (91-100 of 174) with videos related to
Sort By:
Pageof 18
Chemical Communications (Cambridge, England)|June 19, 2014
Large-scale dissipative particle dynamics simulations of self-assembled amphiphilic systemsXuejin Li, Yu-Hang Tang, Haojun Liang, et al.Annals of Biomedical Engineering|January 15, 2014
Computational biorheology of human blood flow in health and diseaseDmitry A Fedosov, Ming Dao, George Em Karniadakis, et al.Neural Networks : the Official Journal of the International Neural Network Society|December 30, 2023
TransformerG2G: Adaptive time-stepping for learning temporal graph embeddings using transformersAlan John Varghese, Aniruddha Bora, Mengjia Xu, et al.Microvascular Research|June 7, 2011
Predicting dynamics and rheology of blood flow: A comparative study of multiscale and low-dimensional models of red blood cellsWenxiao Pan, Dmitry A Fedosov, Bruce Caswell, et al.Plos Computational Biology|October 30, 2016
MD/DPD Multiscale Framework for Predicting Morphology and Stresses of Red Blood Cells in Health and DiseaseHung-Yu Chang, Xuejin Li, He Li, et al.Plos Computational Biology|January 18, 2017
A General Shear-Dependent Model for Thrombus FormationAlireza Yazdani, He Li, Jay D Humphrey, et al.Nature Communications|June 14, 2024
Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systemsKatiana Kontolati, Somdatta Goswami, George Em Karniadakis, et al.Nature Computational Science|January 4, 2024
Discovering and forecasting extreme events via active learning in neural operatorsEthan Pickering, Stephen Guth, George Em Karniadakis, et al.Scientific Reports|August 22, 2023
Physics-informed neural networks for predicting gas flow dynamics and unknown parameters in diesel enginesKamaljyoti Nath, Xuhui Meng, Daniel J Smith, et al.Smart Health (Amsterdam, Netherlands)|March 2, 2026
Patient-specific deep offline artificial pancreas for blood glucose regulation in type 1 diabetesYixiang Deng, Kevin Arao, Christos S Mantzoros, et al.Pageof 18