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An attribution technique distributes the prediction score (e.g. sentiment or prevalence of disease) of a model for a specific input (e.g. paragraph of text or image) to its base features (e.g. words or pixels); the attribution to a base feature can be interpreted as its contribution to the prediction.
Apr 3, 2020 · We propose a new technique called \emph{Blur Integrated Gradients}. This technique has several advantages over other methods. First, it can tell ...
For vision tasks, attribution techniques attribute the prediction of a network to the pixels of the input image. We propose a new technique called Blur.
We propose a new technique called \emph{Blur Integrated Gradients} that produces attributions in both space and in scale. Furthermore, we use the scale-space ...
A new technique called Blur Integrated Gradients (Blur IG) is proposed, which can tell at what scale a network recognizes an object and satisfies the ...
We study the attribution problem for deep networks applied to perception tasks. For vision tasks, attribution techniques attribute the prediction of a ...
A series of explanation methods (e.g., gradient-based saliency/attribution map approaches [21,22,29,33,36,38,43, 46] as well as many that are not based on ...
Jan 18, 2021 · As a group, go to the column labeled “Your Company” and rank on a scale of 1 to 5 how well your company serves each of these attributes—one by ...
Scale is the spatial and temporal attribution of the research-objects or research-process. ... The Spatial and Temporal Attribution of the Geo-Info-TUPU are the ...