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README.md

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-Scripts and modules for the in-progress revision of the preprint, ["A framework for variational inference and data assimilation of soil biogeochemical models using state space approximations and normalizing flows"](https://essopenarchive.org/doi/full/10.1002/essoar.10512103.7).
+This repository stores the collection of scripts and modules tied to the in-progress revision of the preprint, ["A framework for variational inference and data assimilation of soil biogeochemical models using state space approximations and normalizing flows"](https://essopenarchive.org/doi/full/10.1002/essoar.10512103.7).
 
-Pardon the barebones README. 
+Neural moving average flow Python experiment scripts and dependent modules located in "pytorch_sbm_sde_vi" folder. Experiment scripts correspond to the various "learn... .py" files. To replicate an individual experiment, such as a fixed-$\theta$ or or joint $\theta, x$ inference (the use of joint here signifying optimization of both differential equation soil biogeochemical model $\theta$ and hidden neural network $x$ parameters),  run the script associated with the experiment. "learn_NN..." scripts correspond to fixed-$\theta$ flow experiments, while "learn_theta..." scripts correspond to joint inference experiments. Synthetic data used for inference conditioning is located in the "pytorch_sbm_sde_vi/generated_data" folder, while scripts sourcing the synthetic data are in the "pytorch_sbm_sde_vi/python_notebooks" folder. Code associated with the `hamiltorch` SSM-NUTS benchmarking is labeled with "mcmc_..." in the filename.