Neural Activations & Dataset Examples
"Neural Representations" is a category of Explainable AI methods that explore how models represent their inputs to make their predictions. A great first step to several methods in this category is to understand the neural activations table/matrix. This video is a gentle introduction to collecting activations, and then how to use them for an explainability method called "Dataset Examples" which can be seen in action in the OpenAI Microscope (https://microscope.openai.com/models).
Introduction (0:00)
Collecting activations of output neurons (1:00)
Getting activations of multiple input example (3:24)
Sorting the activation matrix (4:25)
Collecting all activations (5:28)
OpenAI Microscope and Dataset Examples (7:33)
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