Method and device for learning artificial intelligence model to estimating epistemic uncertainty based on single model

A single model-based learning device for estimating uncertainty of an artificial intelligence (AI) model, the single model-based learning device comprising:

• a memory configured to store at least one instruction;
• and
• a processor configured to execute the at least one instruction stored in the memory,
• wherein the processor is further configured to:
• based on a result value generated from a feature network, generate an output distribution from a base network and generate a transformed output distribution from a transformed network that is generated by reflecting adaptive noise in the base network,
• calculate a ground truth loss based on a difference between a ground truth distribution and the output distribution and a similarity loss based on a difference between the output distribution and the transformed output distribution, and
• train the AI model consisting of the feature network and the base network by updating a weight of the feature network and the base network through backpropagation of the ground truth loss and the similarity loss.