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Chaos (Woodbury, N.Y.)|April 25, 2023
Interpretable polynomial neural ordinary differential equationsColby Fronk, Linda PetzoldChaos (Woodbury, N.Y.)|November 7, 2025
The vanishing gradient problem for stiff neural differential equationsColby Fronk, Linda PetzoldChaos (Woodbury, N.Y.)|March 25, 2025
Training stiff neural ordinary differential equations with explicit exponential integration methodsColby Fronk, Linda PetzoldChaos (Woodbury, N.Y.)|July 18, 2025
Training stiff neural ordinary differential equations with explicit rational Taylor series methodsColby Fronk, Linda PetzoldChaos (Woodbury, N.Y.)|December 13, 2024
Training stiff neural ordinary differential equations with implicit single-step methodsColby Fronk, Linda PetzoldPlos Computational Biology|October 10, 2024
Bayesian polynomial neural networks and polynomial neural ordinary differential equationsColby Fronk, Jaewoong Yun, Prashant Singh, et al.The Journal of Chemical Physics|February 17, 2017
Reaction rates for reaction-diffusion kinetics on unstructured meshesStefan Hellander, Linda PetzoldJournal of Biological Rhythms|August 8, 2018
Model-based Inference of a Directed Network of Circadian NeuronsDavid McBride, Linda PetzoldPhysical Review. E|February 13, 2016
Reaction rates for a generalized reaction-diffusion master equationStefan Hellander, Linda PetzoldComputer Methods in Applied Mechanics and Engineering|October 2, 2009
Slow Scale Tau-leaping MethodYang Cao, Linda PetzoldPageof 5