Abstract: Systems and methods for identifying a personalized prior within a generative model's latent vector space based on a set of images of a given subject. In some examples, the present technology may further include using the personalized prior to confine the inputs of a generative model to a latent vector space associated with the given subject, such that when the model is tasked with editing an image of the subject (e.g., to perform inpainting to fill in masked areas, improve resolution, or deblur the image), the subject's identifying features will be reflected in the images the model produces.

Abstract: Systems and methods for identifying a personalized prior within a generative model's latent vector space based on a set of images of a given subject. In some examples, the present technology may further include using the personalized prior to confine the inputs of a generative model to a latent vector space associated with the given subject, such that when the model is tasked with editing an image of the subject (e.g., to perform inpainting to fill in masked areas, improve resolution, or deblur the image), the subject's identifying features will be reflected in the images the model produces.

Abstract: Systems and methods for identifying a personalized prior within a generative model's latent vector space based on a set of images of a given subject. In some examples, the present technology may further include using the personalized prior to confine the inputs of a generative model to a latent vector space associated with the given subject, such that when the model is tasked with editing an image of the subject (e.g., to perform inpainting to fill in masked areas, improve resolution, or deblur the image), the subject's identifying features will be reflected in the images the model produces.

Abstract: Aspects of the technology described herein improve the clarity of information provided in automatically generated notifications, such as reminders, tasks, alerts or other messages or communications provided to a user. The clarity may be improved through augmentations that provide additional information or specificity to the user. For example, instead of providing a notification reminding the user, “remember to send the slides before the meeting,” the user may be provided with a notification reminding the user “remember to send the updated sales presentation before the executive committee meeting on Tuesday. The augmentation may take several forms including substituting one word in the notification with another more specific word, adding additional content such as a word or phrase to the notification without altering the existing content, and/or by rephrasing the content for grammatical correctness and/or clarity.

Abstract: Aspects of the technology described herein improve the clarity of information provided in automatically generated notifications, such as reminders, tasks, alerts or other messages or communications provided to a user. The clarity may be improved through augmentations that provide additional information or specificity to the user. For example, instead of providing a notification reminding the user, “remember to send the slides before the meeting,” the user may be provided with a notification reminding the user “remember to send the updated sales presentation before the executive committee meeting on Tuesday. The augmentation may take several forms including substituting one word in the notification with another more specific word, adding additional content such as a word or phrase to the notification without altering the existing content, and/or by rephrasing the content for grammatical correctness and/or clarity.