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data-driven-modeling

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ronceray / StochasticForceInference

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Learn stochastic differential equations (Langevin dynamics: drift/force and diffusion) from time series and trajectory data. Python + JAX.

python time-series statistical-inference stochastic-differential-equations system-identification sparse-regression drift-diffusion biophysics stochastic-processes cell-migration langevin-dynamics jax active-matter entropy-production fokker-planck single-particle-tracking kramers-moyal equation-discovery data-driven-modeling stochastic-thermodynamics
  • Updated Nov 6, 2026
  • Python

FedejGon / NN-CC

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This repository contains the codes for framework for equation discovery by combining Neural Networks with Characteristic Curves (NN-CC), Symmetry Constraints, and Post-Symbolic Regression (Post-SR). It also incorporates implementations of SINDy and pySR within the CC-based formalism.

symbolic-regression sparse-regression interpretable-neural-networks symmetries equation-discovery data-driven-modeling nonlinear-system-identification identifiability-issues uniqueness-of-the-representation adding-domain-knowledge
  • Updated Feb 2, 2026
  • Python

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