3 papers
q-bio.QM2026
Data-driven discovery of dynamical models in biology
Bartosz Prokop, Lendert Gelens
Dynamical systems theory provides a mathematical framework for describing how interacting biological components evolve over time and space, from molecular oscillators to large-scal…
cs.LG2025
Machine learning identifies nullclines in oscillatory dynamical systems
Bartosz Prokop, Jimmy Billen, Nikita Frolov +1
We introduce CLINE (Computational Learning and Identification of Nullclines), a neural network-based method that uncovers the hidden structure of nullclines from oscillatory time s…
nlin.AO2024
Enhancing model identification with SINDy via nullcline reconstruction
Bartosz Prokop, Nikita Frolov, Lendert Gelens
Many dynamical systems exhibit oscillatory behavior that can be modeled with differential equations. Recently, these equations have increasingly been derived through data-driven me…