Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using a neural network to predict locations of feeders in an electrical power grid. One of the methods includes training a generative adversarial network comprising a generator and a discriminator; and generating, by the generator, from input images, output images with feeder metadata that represents predicted locations of feeder assets, including receiving by the generator a first input image and generating by the generator a corresponding first output image with first feeder data that identifies one or more feeder assets and their respective locations, wherein the one or more feeder assets had not been identified in any input to the generator.

Abstract: Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium, including a method for providing content. A request for content is received from a user device. One or more candidate content items that are responsive to the request are identified from an inventory of content items. For each candidate content item, an expected performance measure associated with a respective candidate content item is determined. The expected performance measure for each respective candidate content item is compared to a predetermined threshold. When none of the candidate content items have an expected performance measure that exceeds the threshold, a notification is generated, including generating one or more queries, responsive to the request for inclusion in the notification. The notification is provided responsive to the request and for presentation to the user in lieu of a content item.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using a neural network to predict locations of feeders in an electrical power grid. One of the methods includes training a generative adversarial network comprising a generator and a discriminator; and generating, by the generator, from input images, output images with feeder metadata that represents predicted locations of feeder assets, including receiving by the generator a first input image and generating by the generator a corresponding first output image with first feeder data that identifies one or more feeder assets and their respective locations, wherein the one or more feeder assets had not been identified in any input to the generator.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting locations of utility assets. One of the methods includes receiving an input image of an area in a first geographical region; generating, from the input image and using a generative adversarial network, a corresponding reference image; and generating, by an object detection model and from the reference image, an output that identifies respective locations of one or more utility assets with reference to the input image.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a representation of an electric power grid. One of the methods includes obtaining respective datasets, identifying one or more predictive models for each of the respective datasets that are each configured to processes a category of data to generate an output that specifies a partial representation of the electric power grid; and aggregating the respective outputs in accordance with a set of predetermined rules to generate a final representation of the electric power grid.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting locations of utility assets. One of the methods includes receiving an input image of an area in a first geographical region; generating, from the input image and using a generative adversarial network, a corresponding reference image; and generating, by an object detection model and from the reference image, an output that identifies respective locations of one or more utility assets with reference to the input image.

Abstract: Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium, including a method for providing content. A request for content is received from a user device. One or more candidate content items that are responsive to the request are identified from an inventory of content items. For each candidate content item, an expected performance measure associated with a respective candidate content item is determined. The expected performance measure for each respective candidate content item is compared to a predetermined threshold. When none of the candidate content items have an expected performance measure that exceeds the threshold, a notification is generated, including generating one or more queries, responsive to the request for inclusion in the notification. The notification is provided responsive to the request and for presentation to the user in lieu of a content item.

Abstract: Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium, including a method for providing content. A request for content is received from a user device. One or more candidate content items that are responsive to the request are identified from an inventory of content items. For each candidate content item, an expected performance measure associated with a respective candidate content item is determined. The expected performance measure for each respective candidate content item is compared to a predetermined threshold. When none of the candidate content items have an expected performance measure that exceeds the threshold, a notification is generated, including generating one or more queries, responsive to the request for inclusion in the notification. The notification is provided responsive to the request and for presentation to the user in lieu of a content item.