Calibration using differential machine learning

A computing system comprising processing circuitry and a storage device, wherein the processing circuitry has access to the storage device and is configured to:

• identify, based on a textual description, a model that generates an output based on a set of inputs, wherein the inputs include a plurality of parameters;
• select a first plurality of parameter values;
• assemble a set of training samples by observing outputs generated by the model in response to each of the first plurality of parameter values;
• train, based on the set of training samples, a surrogate model, wherein the surrogate model is trained to predict outputs of the model;
• generate, using the surrogate model, predicted outputs of the model, wherein each of the predicted outputs of the model is based on a different parameter value in a second plurality of parameter values;
• select, based on the predicted outputs of the model, a desired parameter value;
• and
• apply the model, using the desired parameter value, to predict a value of interest for an input value.

A non-transitory computer-readable medium comprising instructions that, when executed, configure processing circuitry of a computing system to:

• identify, based on a textual description, a model that generates an output based on a set of inputs, wherein the inputs include a plurality of parameters;
• select a first plurality of parameter values;
• assemble a set of training samples by observing outputs generated by the model in response to each of the first plurality of parameter values;
• train, based on the set of training samples, a surrogate model, wherein the surrogate model is trained to predict outputs of the model;
• generate, using the surrogate model, predicted outputs of the model, wherein each of the predicted outputs of the model is based on a different parameter value in a second plurality of parameter values;
• select, based on the predicted outputs of the model, a desired parameter value;
• and
• apply the model, using the desired parameter value, to predict a value of interest for an input value.