Adrian Buganza Tepole

According to our database, Adrian Buganza Tepole authored at least 22 papers between 2019 and 2026.

Collaborative distances:

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

2026

Stable Long-Horizon Neural ODE Reduced-Order Models via Learned Feedback for Biological Growth and Remodeling.

Joel Laudo, Adrian Buganza Tepole

CoRR, April, 2026

A Differentiable Framework for Gradient Enhanced Damage with Physics-Augmented Neural Networks in JAX-FEM.

Mark Wilkinson, Amirhossein Amiri-Hezaveh, Adrian Buganza Tepole

CoRR, April, 2026

Differentiable neural network representation of multi-well, locally-convex potentials.

Reese E. Jones, Adrian Buganza Tepole, Jan Niklas Fuhg

J. Comput. Phys., 2026

Subcutaneous tissue structural feature identification using unsupervised machine learning.

Sourav Das, Melissa C. Brindise, Jordanna M. Payne, Luis Solorio, Adrian Buganza Tepole, Pavlos P. Vlachos

Comput. Biol. Medicine, 2026

2025

A Physics-Informed Deep Learning Deformable Medical Image Registration Method Based on Neural ODEs.

Amirhossein Amiri-Hezaveh, Shelly Tan, Qing Deng, David M. Umulis, Lauren Cunniff, Johannes Weickenmeier, Adrian Buganza Tepole

Int. J. Comput. Vis., September, 2025

Fully data-driven inverse hyperelasticity with hyper-network neural ODE fields.

Vahidullah Tac, Amirhossein Amiri-Hezaveh, Manuel K. Rausch, Grace N. Bechtel, Francisco Sahli Costabal, Adrian Buganza Tepole

CoRR, June, 2025

A universal material model subroutine for soft matter systems.

Mathias Peirlinck, Juan A. Hurtado, Manuel K. Rausch, Adrian Buganza Tepole, Ellen Kuhl

Eng. Comput., April, 2025

Polyconvex Physics-Augmented Neural Network Constitutive Models in Principal Stretches.

Adrian Buganza Tepole, Asghar A. Jadoon, Manuel K. Rausch, Jan Niklas Fuhg

CoRR, March, 2025

Generative hyperelasticity with physics-informed probabilistic diffusion fields.

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

Eng. Comput., February, 2025

2024

Physics-Informed Neural Network for Scalable Soft Multi-Actuator Systems.

Carly A. Mendenhall, Jonathan Hardan, Trysta D. Chiang, Laura H. Blumenschein, Adrian Buganza Tepole

Proceedings of the 7th IEEE International Conference on Soft Robotics, 2024

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

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