Adrian Buganza Tepole

According to our database, Adrian Buganza Tepole authored at least 13 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Computational mechanobiology model evaluating healing of postoperative cavities following breast-conserving surgery.

Zachary Harbin, David Sohutskay, Emma Vanderlaan, Muira Fontaine, Carly A. Mendenhall, Carla Fisher, Sherry Voytik-Harbin, Adrian Buganza Tepole

Comput. Biol. Medicine, October, 2023

Mechano-biological and bio-mechanical pathways in cutaneous wound healing.

Marco Pensalfini, Adrian Buganza Tepole

PLoS Comput. Biol., March, 2023

Generative Hyperelasticity with Physics-Informed Probabilistic Diffusion Fields.

Vahidullah Tac, Manuel K. Rausch, Ilias Bilionis, Francisco Sahli Costabal, Adrian Buganza Tepole

CoRR, 2023

Data-driven anisotropic finite viscoelasticity using neural ordinary differential equations.

Vahidullah Tac, Manuel K. Rausch, Francisco Sahli Costabal, Adrian Buganza Tepole

CoRR, 2023

Benchmarks for physics-informed data-driven hyperelasticity.

Vahidullah Tac, Kevin Linka, Francisco Sahli Costabal, Ellen Kuhl, Adrian Buganza Tepole

CoRR, 2023

2022

Special Issue: Imaging-based methods in computational medicine.

Adrian Buganza Tepole, Johannes Weickenmeier, Maria A. Holland, Rafael Grytz

Eng. Comput., 2022

Data-driven modeling of the mechanical behavior of anisotropic soft biological tissue.

Vahidullah Tac, Vivek D. Sree, Manuel K. Rausch, Adrian Buganza Tepole

Eng. Comput., 2022

PDE-constrained shape registration to characterize biological growth and morphogenesis from imaging data.

Aishwarya Pawar, Linlin Li, Arun Gosain, David M. Umulis, Adrian Buganza Tepole

Eng. Comput., 2022

Elasticity Solver in Minecraft for Learning Mechanics of Materials by Gaming.

Zachariah P. Beck, Brandon Alpert, Alexander J. Bowman, William R. Watson, Adrian Buganza Tepole

CoRR, 2022

2021

Automatically Polyconvex Strain Energy Functions using Neural Ordinary Differential Equations.

Vahidullah Tac, Francisco Sahli Costabal, Adrian Buganza Tepole

CoRR, 2021

Predicting the Mechanical Properties of Fibrin Using Neural Networks Trained on Discrete Fiber Network Data.

Yue Leng, Sarah Calve, Adrian Buganza Tepole

CoRR, 2021

2020

Improving Reconstructive Surgery Design using Gaussian Process Surrogates to Capture Material Behavior Uncertainty.

Casey Stowers, Taeksang Lee, Ilias Bilionis, Arun Gosain, Adrian Buganza Tepole

CoRR, 2020

2019

Integrating machine learning and multiscale modeling - perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences.

Mark S. Alber, Adrian Buganza Tepole, William R. Cannon, Suvranu De, Salvador Dura-Bernal, Krishna C. Garikipati, George E. Karniadakis, William W. Lytton, Paris Perdikaris, Linda R. Petzold, Ellen Kuhl

npj Digit. Medicine, 2019