Modular autoencoder model for manufacturing process parameter estimation

A system for estimating parameters of interest from a combination of available channels of measurement data from an optical metrology platform by estimating retrievable quantities of information content using a subset of a plurality of input models of a modular autoencoder model based on the available channels, the system comprising:

• the plurality of input models, the plurality of input models configured to compress a plurality of inputs based on the available channels such that the plurality of inputs are suitable for combination with each other;
• and
• a common model of the modular autoencoder model configured to combine the compressed inputs and generate low dimensional data in a latent space based on the combined compressed inputs,
• wherein the low dimensional data estimates the retrievable quantities, and
• wherein the low dimensional data in the latent space is configured to be used by one or more additional models to generate approximations of the plurality of inputs and/or estimate a parameter based on the low dimensional data.

A non-transitory computer readable medium having instructions thereon, the instructions configured to cause a computer to execute a modular autoencoder model for parameter estimation, the instructions causing operations comprising:

• causing a plurality of input models to compress a plurality of inputs such that the plurality of inputs are suitable for combination with each other;
• and
• causing a common model to combine the compressed inputs and generate low dimensional data in a latent space based on the combined compressed inputs, the low dimensional data in the latent space configured to be used by one or more additional models to generate the approximations of the one or more inputs and/or predict the parameter based on the low dimensional data,
• wherein the common model is configured to combine the compressed inputs and generate the low dimensional data regardless of which ones of the plurality of inputs are combined by the common model.