Systems and methods to use neural networks for model transformations

A system for transforming an input model into a neural network model, the system comprising:

• one or more memory units for storing instructions;
• and
• one or more processors configured to execute the instructions to perform operations comprising:
• receiving input data comprising the input model;
• obtaining dataset model output by applying the input model to an input dataset;
• storing the generated dataset model output and at least one of:
• input model features;
• or a map of the input model features;
• generating a plurality of candidate neural network models based on the input model features;
• tuning the plurality of candidate neural network models by adjusting at least one of a plurality of hidden layers, a plurality of inputs, or a type of layer during tuning such that at least one of the input model features is reproduced;
• selecting a neural network model from the plurality of candidate neural network models based on one or more model selection criteria;
• and
• returning the selected neural network model.

A method for transforming an input model into a neural network model, the method comprising:

• obtaining dataset model output by applying an input model to an input dataset, the input model having a plurality of input model features;
• generating a plurality of candidate neural network models based on the input model features;
• tuning the plurality of candidate neural network models by adjusting at least one of a plurality of hidden layers, a plurality of inputs, or a type of layer during tuning such that at least one of the input model features is reproduced;
• selecting a neural network model from the plurality of candidate neural network models based on one or more model selection criteria;
• and
• returning the selected neural network model.

A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, are configured to cause the at least one processor to perform operations comprising:

• obtaining dataset model output by applying an input model to an input dataset, the input model having a plurality of input model features;
• generating a plurality of candidate neural network models based on the input model features;
• tuning the plurality of candidate neural network models by adjusting at least one of a plurality of hidden layers, a plurality of inputs, or a type of layer during tuning such that at least one of the input model features is reproduced;
• selecting a neural network model from the plurality of candidate neural network models based on one or more model selection criteria, a model type of the selected neural network model being different from a model type of the input model;
• and
• returning the selected neural network model.