Patents by Inventor Jonathan LORRAINE

Jonathan LORRAINE has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • DENOISING DATA USING DIFFERENT DIFFUSION NEURAL NETWORKS
    Publication number: 20260087601
    Abstract: Apparatuses, systems, and techniques to cause neural network inferencing or training data to be denoised are described. In at least one embodiment, denoising of neural network inferencing or training data may be performed based, at least in part, on identifying different types of inferencing or training data within the neural network inferencing or training data to be denoised separately using a corresponding number of diffusion neural networks.
    Type: Application
    Filed: September 26, 2024
    Publication date: March 26, 2026
    Inventors: James Robert Lucas, Jonathan Lorraine, Karsten Julian Kreis, Yanke Song, Weili Nie
  • 3D model generation using multimodal generative AI
    Patent number: 12555343
    Abstract: In various examples, systems and methods are disclosed relating to generating an output 3D latent representation by encoding, using a text encoder, a text prompt and encoding, using a 2D/3D encoder, a 2D image of an object or a 3D representation of the object. A 3D output is generated by applying the output 3D latent representation to a decoder. A reconstruction loss and a SDS loss are determined for the 3D output. At least one of the text encoder, the 2D/3D encoder, and the decoder is updated using the reconstruction loss and the SDS loss.
    Type: Grant
    Filed: March 29, 2024
    Date of Patent: February 17, 2026
    Assignee: NVIDIA Corporation
    Inventors: Cheng Xie, Jonathan Lorraine, Xiaohui Zeng, James Lucas, Jun Gao, Sanja Fidler
  • 3D MODEL GENERATION USING MULTIMODAL GENERATIVE AI
    Publication number: 20250308183
    Abstract: In various examples, systems and methods are disclosed relating to generating an output 3D latent representation by encoding, using a text encoder, a text prompt and encoding, using a 2D/3D encoder, a 2D image of an object or a 3D representation of the object. A 3D output is generated by applying the output 3D latent representation to a decoder. A reconstruction loss and a SDS loss are determined for the 3D output. At least one of the text encoder, the 2D/3D encoder, and the decoder is updated using the reconstruction loss and the SDS loss.
    Type: Application
    Filed: March 29, 2024
    Publication date: October 2, 2025
    Applicant: NVIDIA Corporation
    Inventors: Cheng XIE, Jonathan LORRAINE, Xiaohui ZENG, James LUCAS, Jun GAO, Sanja FIDLER