Distance to Modelled Embedding

DIME: Detecting Out-of-Distribution Examples with Distance to Modelled Embedding DIME is a powerful tool in machine learning that helps detect out-of-distribution examples during prediction time. In order to understand what DIME does, we first need to understand what it means to train a neural network and how it works. When we train a neural network, we feed it a set of training data drawn from some high-dimensional distribution in data space X. The neural network then transforms this training