CPC G06N 3/088 (2013.01) [G06F 18/211 (2023.01); G06N 7/08 (2013.01); G06N 20/00 (2019.01)] | 20 Claims |
1. A method for training a constrained generative model, the method comprising:
receiving a set of data samples from a first distribution;
identifying a set of constraints from a second distribution; and
training a generative model based on the set of data samples and the set of constraints, wherein:
the generative model is a neural network comprising hidden units; and
training the generative model comprises:
training the generative model on the set of data samples;
updating the generative model to add a set of new hidden units and connections to the generative model; and
training the generative model based on the set of constraints by modifying weights for the set of new hidden units.
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