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Distributing attribution algorithm calculations across multiple processors, machines, or GPUs to speed up processing.
Distinct from Distributed Computing: Distinct from Distributed Computing: specifically for distributing attribution computations rather than general distributed processing.
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Captum is an open-source library for explaining model predictions by attributing them to input features, neurons, and layers using gradient-based and perturbation-based methods. It provides a modular framework for implementing, evaluating, and combining a range of explanation techniques, including gradient-based attribution, perturbation-based analysis, game-theoretic Shapley value approximation, and surrogate model explanations, with support for parallelization and noise stabilization. The library distinguishes itself through its breadth of attribution methods and its support for advanced in
Distributes attribution algorithm calculations across multiple processors or GPUs to speed up processing.