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1. linf linf Public

   Lagrangian INFerence: work in progress using mixture density networks to learn dynamics from surface drifter data.

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2. NS2D NS2D Public

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3. qg_closure qg_closure Public

   Code to accompany the paper "Stochasticity and probabilistic trajectory scoring are essential for data-driven closures of chaotic systems".

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4. BMC BMC Public

   Python code for 'Bayesian comparison of stochastic models of dispersion' -- https://doi.org/10.1017/jfm.2022.472.

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5. transition_density transition_density Public

   Python code for 'Inferring ocean transport statistics with probabilistic neural networks', available at https://doi.org/10.1029/2023MS003718.

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6. lorenz_param lorenz_param Public

   Python code to accompany the article "Stochastic parameterisation: the importance of nonlocality and memory" available at https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2025MS005223.

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