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Recent Talks & Demos are for members only
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We demonstrate a modelβagnostic method to infer an image classifierβs learned features using only the model, and present our analysis library and dashboard.
At Leap Labs we have developed a novel approach to AI interpretability. Our methods are model agnostic, and donβt require access to the original training data. We can extract information on what a neural network has learned directly from the model itself, and weβre packaging this capability up into a library and web dashboard for anyone to use. Weβd love to show you what we have so far with our initial support for image classification models.
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