176 citations · 392 across the 14 of their papers we have counts for
17 papers
Hyperparameter selection for equation learning with biologically-informed neural networks
William Lavery, Jodie A. Cochrane, John T. Nardini +1
Biologically-informed neural networks (BINNs) have emerged as a flexible subclass of physics-informed neural networks (PINNs) for learning terms in partial differential equations f…
Spatial Model Selection and Uncertainty Quantification: Comparing Continuous and Discrete Wound Healing Models
John T. Nardini, Jana L. Gevertz
All data-driven modeling tasks (e.g., parameter estimation, uncertainty quantification, and data forecasting) require the selection of a mathematical model. An overlooked aspect of…
Physics-Informed Neural Networks for Biological Reaction-Diffusion Systems
William Lavery, Jodie A. Cochrane, Christian Olesen +3
Physics-informed neural networks (PINNs) provide a powerful framework for learning governing equations of dynamical systems from data. Biologically-informed neural networks (BINNs)…
Quantifying topological features and irregularities in zebrafish patterns using the sweeping-plane filtration
Nour Khoudari, John Nardini, Alexandria Volkening
Complex patterns emerge across a wide range of biological systems. While such patterns often exhibit remarkable robustness, variation and irregularity exist at multiple scales and…
Enhancing generalizability of model discovery across parameter space with multi-experiment equation learning (ME-EQL)
Maria-Veronica Ciocanel, John T. Nardini, Kevin B. Flores +3
Agent-based modeling (ABM) is a powerful tool for understanding self-organizing biological systems, but it is computationally intensive and often not analytically tractable. Equati…
SSRCA: a novel machine learning pipeline to perform sensitivity analysis for agent-based models
Edward H. Rohr, John T. Nardini
Agent-based models (ABMs) are widely used in biology to understand how individual actions scale into emergent population behavior. Modelers employ sensitivity analysis (SA) algorit…