241 citations · 925 across the 11 of their papers we have counts for
11 papers
PINN-FEM: A Hybrid Approach for Enforcing Dirichlet Boundary Conditions in Physics-Informed Neural Networks
Nahil Sobh, Rini Jasmine Gladstone, Hadi Meidani
Physics-Informed Neural Networks (PINNs) solve partial differential equations (PDEs) by embedding governing equations and boundary/initial conditions into the loss function. Howeve…
Error Estimates and Physics Informed Augmentation of Neural Networks for Thermally Coupled Incompressible Navier Stokes Equations
Shoaib Goraya, Nahil Sobh, Arif Masud
Physics Informed Neural Networks (PINNs) are shown to be a promising method for the approximation of Partial Differential Equations (PDEs). PINNs approximate the PDE solution by mi…
Continual Learning for Tumor Classification in Histopathology Images
Veena Kaustaban, Qinle Ba, Ipshita Bhattacharya +6
Recent years have seen great advancements in the development of deep learning models for histopathology image analysis in digital pathology applications, evidenced by the increasin…
Enhanced physics-informed neural networks for hyperelasticity
Diab W. Abueidda, Seid Koric, Erman Guleryuz +1
Physics-informed neural networks have gained growing interest. Specifically, they are used to solve partial differential equations governing several physical phenomena. However, ph…
A deep learning energy method for hyperelasticity and viscoelasticity
Diab W. Abueidda, Seid Koric, Rashid Abu Al-Rub +3
The potential energy formulation and deep learning are merged to solve partial differential equations governing the deformation in hyperelastic and viscoelastic materials. The pres…
Phase Imaging with Computational Specificity (PICS) for measuring dry mass changes in sub-cellular compartments
Mikhail E. Kandel, Yuchen R. He, Young Jae Lee +7
Due to its specificity, fluorescence microscopy (FM) has become a quintessential imaging tool in cell biology. However, photobleaching, phototoxicity, and related artifacts continu…