E-LIB Suche - Ergebnisse für: Sahli-Costabal, Francisco

1

Benchmarking physics-informed frameworks for data-driven hy..:

Taç, Vahidullah ; Linka, Kevin ; Sahli-Costabal, Francisco..
Computational Mechanics. 73 (2023) 1 - p. 49-65 , 2023

Link: https://doi.org/10.1007/..

2

Classifying Drugs by their Arrhythmogenic Risk Using Machin..:

Sahli-Costabal, Francisco ; Seo, Kinya ; Ashley, Euan.
Biophysical Journal. 118 (2020) 5 - p. 1165-1176 , 2020

Link: https://doi.org/10.1016/..

3

Machine learning modeling of lung mechanics: Assessing the ..:

Barahona, José ; Sahli Costabal, Francisco ; Hurtado, Daniel E.
Computer Methods and Programs in Biomedicine. 243 (2024) - p. 107888 , 2024

Link: https://doi.org/10.1016/..

4

Δ-PINNs: Physics-informed neural networks on complex geomet..:

Sahli Costabal, Francisco ; Pezzuto, Simone ; Perdikaris, Paris
Engineering Applications of Artificial Intelligence. 127 (2024) - p. 107324 , 2024

Link: https://doi.org/10.1016/..

5

Generative hyperelasticity with physics-informed probabilis..:

Taç, Vahidullah ; Rausch, Manuel K. ; Bilionis, Ilias..
Engineering with Computers. , 2024

Link: https://doi.org/10.1007/..

6

Physics-informed neural networks for parameter estimation i..:

Garay, Jeremías ; Dunstan, Jocelyn ; Uribe, Sergio.
Computers in Biology and Medicine. 178 (2024) - p. 108706 , 2024

Link: https://doi.org/10.1016/..

7

The Fibrotic Kernel Signature: Simulation-Free Prediction o..:

, In: Functional Imaging and Modeling of the Heart; Lecture Notes in Computer Science,

Sahli Costabal, Francisco ; Banduc, Tomás ; Gander, Lia. - p. 87-96 , 2023

Link: https://doi.org/10.1007/..

8

On the Accuracy of Eikonal Approximations in Cardiac Electr..:

, In: Functional Imaging and Modeling of the Heart; Lecture Notes in Computer Science,

Gander, Lia ; Krause, Rolf ; Weiser, Martin.. - p. 137-146 , 2023

Link: https://doi.org/10.1007/..

9

Data-driven anisotropic finite viscoelasticity using neural..:

Taç, Vahidullah ; Rausch, Manuel K. ; Sahli Costabal, Francisco.
Computer Methods in Applied Mechanics and Engineering. 411 (2023) - p. 116046 , 2023

Link: https://doi.org/10.1016/..

10

WarpPINN: Cine-MR image registration with physics-informed ..:

Arratia López, Pablo ; Mella, Hernán ; Uribe, Sergio..
Medical Image Analysis. 89 (2023) - p. 102925 , 2023

Link: https://doi.org/10.1016/..

11

Data-driven anisotropic finite viscoelasticity using neural..:

Tac, Vahidullah ; Rausch, Manuel K ; Sahli-Costabal, Francisco.
http://arxiv.org/abs/2302.03598. , 2023

Link: http://arxiv.org/abs/230..

12

Benchmarks for physics-informed data-driven hyperelasticity:

Tac, Vahidullah ; Linka, Kevin ; Sahli-Costabal, Francisco..
http://arxiv.org/abs/2301.10714. , 2023

Link: http://arxiv.org/abs/230..

13

Data-driven tissue mechanics with polyconvex neural ordinar..:

Tac, Vahidullah ; Sahli Costabal, Francisco ; Tepole, Adrian B.
Computer Methods in Applied Mechanics and Engineering. 398 (2022) - p. 115248 , 2022

Link: https://doi.org/10.1016/..

14

Physics-informed neural networks to learn cardiac fiber ori..:

Ruiz Herrera, Carlos ; Grandits, Thomas ; Plank, Gernot...
Engineering with Computers. 38 (2022) 5 - p. 3957-3973 , 2022

Link: https://doi.org/10.1007/..

15

Fast Characterization of Inducible Regions of Atrial Fibril..:

Gander, Lia ; Pezzuto, Simone ; Gharaviri, Ali...
Frontiers in Physiology. 13 (2022) - p. , 2022

Link: https://doi.org/10.3389/..