中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

6626 records (took 0.038 seconds)

    PREDICTING APPLICATION STATES FOR SUPPLEMENTAL CONTENT INSERTION
    63.
    发明申请
    PREDICTING APPLICATION STATES FOR SUPPLEMENTAL CONTENT INSERTION 有权

    公开(公告)号：US20250047910A1

    公开(公告)日：2025-02-06

    申请号：US18363917

    申请日：2023-08-02

    Applicant: Nvidia Corporation

    Inventor： Andrew Fear ,  YuCheng Liu

    IPC: H04N21/234 ,  H04N21/431 ,  H04N21/442

    Abstract: Approaches presented herein provide systems and methods for determining different states for distributed computing processes based on information acquired from underlying hardware. Different tasks may be executed by hardware for a given distributed computing process having a certain hardware configuration and for a given application. Telemetry information may be acquired to identify different states according to the telemetry information independent from underlying application engines. Thereafter, identification of different application states enables prediction of time periods between various application states, which may provide opportunities for additional processing tasks, such as providing supplemental content.

    VARIATIONAL INFERENCING BY A DIFFUSION MODEL
    66.
    发明申请
    VARIATIONAL INFERENCING BY A DIFFUSION MODEL 有权

    公开(公告)号：US20250045892A1

    公开(公告)日：2025-02-06

    申请号：US18593742

    申请日：2024-03-01

    Applicant: NVIDIA Corporation

    Inventor： Morteza Mardani ,  Jiaming Song ,  Jan Kautz ,  Arash Vahdat

    IPC: G06T7/00 ,  G06T3/40 ,  G06T5/70 ,  G06T5/73 ,  G06T5/77

    Abstract: Diffusion models are machine learning algorithms that are uniquely trained to generate high-quality data from an input lower-quality data. For example, they can be trained in the image domain, for example, to perform specific image restoration tasks, such as inpainting (e.g. completing an incomplete image), deblurring (e.g. removing blurring from an image), and super-resolution (e.g. increasing a resolution of an image), or they can be trained to perform image rendering tasks, including 2D-to-3D image generation tasks. However, current approaches to training diffusion models only allow the models to be optimized for a specific task such that they will not achieve high-quality results when used for other tasks. The present disclosure provides a diffusion model that uses variational inferencing to approximate a distribution of data, which allows the diffusion model to universally solve different tasks without having to be re-trained specifically for each task.

    BATCH SCHEDULING FOR EFFICIENT EXECUTION OF MULTIPLE MACHINE LEARNING MODELS
    67.
    发明申请
    BATCH SCHEDULING FOR EFFICIENT EXECUTION OF MULTIPLE MACHINE LEARNING MODELS 有权

    公开(公告)号：US20250045622A1

    公开(公告)日：2025-02-06

    申请号：US18230311

    申请日：2023-08-04

    Applicant: NVIDIA Corporation

    Inventor： Shekhar Dwivedi ,  Rahul Choudhury

    IPC: G06N20/00

    Abstract: Apparatuses, systems, and techniques for efficient profiling, scheduling, and batch execution of multiple machine learning models (MLMs). Efficient batch execution includes obtaining execution metrics characterizing expected utilization of computational resources by the MLMs, and generating at least one batch queue having one or more MLM batches of MLMs with a combined expected utilization not exceeding a threshold utilization, and initiating parallel execution of the MLMs using the generated MLM batches.

    GPU-INITITATED DATA ACCESS OF SCALED STORAGE
    69.
    发明申请
    GPU-INITITATED DATA ACCESS OF SCALED STORAGE 有权

    公开(公告)号：US20250045094A1

    公开(公告)日：2025-02-06

    申请号：US18242682

    申请日：2023-09-06

    Applicant: NVIDIA Corporation

    Inventor： Christopher J. Newburn ,  Zaid Qureshi ,  Vikram Sharma Mailthody ,  Isaac Gelado ,  Wen-Mei Hwu ,  Kiran Modukuri ,  Harish Arora

    IPC: G06F9/48 ,  G06F9/50 ,  G06F9/54

    Abstract: Apparatuses, systems, and techniques to use parallel processing unit(s) (“PPU(s)”) to perform data access(es) in response to data access request(es). The data access(es) may be performed by accessing at least a first portion of data stored in at least a first location of data location(s) if the first location is on a first tier of a plurality of data tiers that is accessible by the PPU(s), and causing server interface(s) to access at least a second portion of the data stored in at least a second location of the data location(s) if the second location is on a second tier of the plurality of data tiers. The data access request(s) may be performed using an API. The data access(es) may be performed by client(s) and the server interface(s) may be implemented by server(s). The client(s) and server(s) may be implemented by node(s), and may be paused and migrated to other node(s) during execution time. The client(s) may implement synchronous and/or asynchronous interfaces.

    TRAILER ANGLE ESTIMATION USING MACHINE LEARNING
    70.
    发明申请
    TRAILER ANGLE ESTIMATION USING MACHINE LEARNING 有权

    公开(公告)号：US20250042416A1

    公开(公告)日：2025-02-06

    申请号：US18363477

    申请日：2023-08-01

    Applicant: NVIDIA Corporation

    Inventor： Ayon SEN

    IPC: B60W50/00 ,  B62D15/02 ,  G06T17/00 ,  G06V10/764 ,  G06V10/82 ,  G06V20/56

    Abstract: In various examples, a trailer angle may be estimated using one or more machine learning models to predict one or more keypoints on the center axis of the trailer drawbar (e.g., a keypoint representing the drawbar junction around which the drawbar pivots, one or more other keypoints along the center axis), back-projecting the predicted keypoint(s) onto a three-dimensional (3D) representation of the ground, and calculating the angle between the longitudinal axis of the towing vehicle and a line or ray formed by or fitted to the projected keypoints. The trailer angle may be estimated at any frame rate. For each frame, keypoints may be predicted from that frame and/or optical flow or some other type of feature tracking may be used to propagate predicted keypoint(s) from a preceding frame in lieu of predicting keypoint(s), and the resulting keypoint(s) may be used to estimate the trailer angle for that frame.

Patent Agency Ranking