The prgram requires tensorflow, numpy, pandas and jax. It has been tested with tesorflow 2.4.0, numpy 1.19.5, pandas 1.0.1 and jax 0.3.14.
Running NeuroComplete requires first creating a config file containing all the configurations required and then calling python query.py to train the model and perform inference. The program automatically generates training and testing data for the H1 setting on a subsample of housing dataset, trains NeuroComplete on the training data and performs inference for H1 average queries.
The file default_config.py contains the default configuration and explanation for each parameter. Running python default_config.py creates a json file containing default values.