These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.
Sparsity
While smoothness and spatial locality capture spatial properties, the individual values shall also be sparse, since few highly important regions are more indicative of a good explanation than several mildly relevant ones. This is why a sparsity metric should be used. Please refer to the reference URL for full formulation.
Related use cases :
Adaptive Neural Connections for Sparsity Learning
Uploaded on Nov 1, 2023Contrastive models like CLIP have been shown to learn robust representations
of images that capture both semantics and style. To leverage these
representations for image generation...
About the metric
You can click on the links to see the associated metrics
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