Data-Driven Discovery of a Hyperelastic Strain-Energy Function for Veins Using Constitutive Artificial Neural Networks
q-bio.QM, physics.bio-ph, physics.comp-ph
Submitted: 2026-10-10
Updated: 2026-10-10
Comments: 26 pages, includes supplementary materials
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
Related papers
- Direct RNA sequence design under codon constraints using expressive tensor-based secondary structure models
- A likelihood-based framework for simultaneously learning both noise and growth dynamics using biologically-informed neural networks
- Can synthetic data reproduce real-world findings in epidemiology? A replication study using adversarial random forests
- Automated Lesion Segmentation of Stroke MRI Using nnU-Net: A Comprehensive External Validation Across Acute and Chronic Lesions
- Imaging-anchored multiomics in cardiovascular disease: integrating cardiac imaging, bulk, single-cell, and spatial transcriptomics
- Resolving satellite-in situ mismatches in Net Primary Production using high-frequency in situ bio-optical observations in the subpolar Northwest Atlantic