GENERATING DISCRETE DATA USING DIFFUSION NEURAL NETWORKS

    公开(公告)号:US20250053786A1

    公开(公告)日:2025-02-13

    申请号:US18366638

    申请日:2023-08-07

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a network output of high dimensional data comprising one or more output tokens. In one aspect, a system comprises a neural network system configured to initialize an analog bit representation of the network output comprising a set of continuous numeric values for each of the output tokens. The neural network system generates an updated analog bit representation that comprises a set of updated continuous numeric values. At each of a plurality of update iterations, the neural network system processes a diffusion input comprising the analog bit representation using a diffusion machine learning model to update the analog bit representation.

Patent Agency Ranking