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Found 4 papers, 1 papers with code
Truthful AI: Developing and governing AI that does not lie
Establishing norms or laws of AI truthfulness will require significant work to: (1) identify clear truthfulness standards; (2) create institutions that can judge adherence to those standards; and (3) develop AI systems that are robustly truthful.
Inability of spatial transformations of CNN feature maps to support invariant recognition
In this paper, we prove that spatial transformations of CNN feature maps cannot align the feature maps of a transformed image to match those of its original, for general affine transformations, unless the extracted features are themselves invariant.
Understanding when spatial transformer networks do not support invariance, and what to do about it
This enables the use of more complex features when predicting transformation parameters.
The problems with using STNs to align CNN feature maps
Spatial transformer networks (STNs) were designed to enable CNNs to learn invariance to image transformations.
