Global Sensitivity Analysis of Four Chamber Heart Hemodynamics Using Surrogate Models. [PDF]
IEEE Trans Biomed Eng, 2022 Computational Fluid Dynamics (CFD) is used to assist in designing artificial valves and planning procedures, focusing on local flow features. However, assessing the impact on overall cardiovascular function or predicting longer-term outcomes may require ...
Karabelas E +9 more
europepmc +3 more sources
Surrogate models based on machine learning methods for parameter estimation of left ventricular myocardium. [PDF]
R Soc Open Sci, 2021 A long-standing problem at the frontier of biomechanical studies is to develop fast methods capable of estimating material properties from clinical data.
Cai L +5 more
europepmc +2 more sources
Human surrogate models of central sensitization: A critical review and practical guide. [PDF]
Eur J Pain, 2021 As in other fields of medicine, development of new medications for management of neuropathic pain has been difficult since preclinical rodent models do not necessarily translate to the clinics. Aside from ongoing pain with burning or shock‐like qualities,
Quesada C +14 more
europepmc +2 more sources
Surrogate models for precessing binary black hole simulations with unequal masses [PDF]
Physical Review Research, 2019 Only numerical relativity simulations can capture the full complexities of binary black hole mergers. These simulations, however, are prohibitively expensive for direct data analysis applications such as parameter estimation.
V. Varma +7 more
semanticscholar +6 more sources
Development of surrogate models in reliability-based design optimization: A review
Mathematical Biosciences and Engineering, 2021 Reliability-based design optimization (RBDO) is applied to handle the unavoidable uncertainties in engineering applications. To alleviate the huge computational burden in reliability analysis and design optimization, surrogate models are introduced to ...
Xiaoke Li +6 more
doaj +2 more sources
Evaluation of POD based surrogate models of fields resulting from nonlinear FEM simulations
Advanced Modeling and Simulation in Engineering Sciences, 2021 Surrogate modelling is a powerful tool to replace computationally expensive nonlinear numerical simulations, with fast representations thereof, for inverse analysis, model-based control or optimization.
Boukje M. de Gooijer +3 more
doaj +2 more sources
Multiple Physics Pretraining for Physical Surrogate Models [PDF]
arXiv.org, 2023 We introduce multiple physics pretraining (MPP), an autoregressive task-agnostic pretraining approach for physical surrogate modeling of spatiotemporal systems with transformers.
Michael McCabe +13 more
semanticscholar +1 more source
Uncertainty-aware Surrogate Models for Airfoil Flow Simulations with Denoising Diffusion Probabilistic Models [PDF]
AIAA Journal, 2023 Leveraging neural networks as surrogate models for turbulence simulation is a topic of growing interest. At the same time, embodying the inherent uncertainty of simulations in the predictions of surrogate models remains very challenging.
Qiang Liu, Nils Thürey
semanticscholar +1 more source
Neural architecture search using network embedding and generative adversarial networks [PDF]
Scientific ReportsSurrogate models are used by recently proposed algorithms as a means of forecasting neural architecture performance. Rather than training the network from scratch, which speeds up evaluation of performance in the search for neural architecture.
Morteza Yousefi +2 more
doaj +2 more sources
Deep Learning-based surrogate models for parametrized PDEs: handling geometric variability through graph neural networks [PDF]
Chaos, 2023 Mesh-based simulations play a key role when modeling complex physical systems that, in many disciplines across science and engineering, require the solution to parametrized time-dependent nonlinear partial differential equations (PDEs).
N. R. Franco +3 more
semanticscholar +1 more source