However,twokeydrawbacks of RPS-l2 are thatthey(i)leadtodisagreement between theoriginally trained networkandthe RPS-l2 regularized network modification and (ii) often yield a static ranking of training data fortest points inthesame class, independent ofthetest point being classified. Inspired by the RPS-l2 approach, we propose an alternative method based on a local Jacobian Taylor expansion (LJE).

Deep learning has made great strides in the applications of image restoration.

Extracting extrusion cylinders from raw 3D geometry has been extensively researched in computer vision, while the processing of 3D data through neural networks has remained a bottleneck.

Thumbnails of dendrites are randomly colored.

How can we build AI systems that can learn any set of individual human values both quickly and safely, avoiding causing harm or violating societal standards for acceptable behavior during the learning process? We explore the effects of representational alignment between humans and AI agents on learning human values.