Patents by Inventor Arthur Deng

Arthur Deng 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).

  • Training generative machine learning models for 3D molecular structure prediction using alignment objectives
    Patent number: 12724948
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a generative model by a machine learning training technique using an alignment objective. In one aspect, a method comprises, at each of a sequence of training steps: obtaining data characterizing a set of one or more molecules for the training step; processing, by the generative model, the data characterizing the set of one or more molecules to generate a plurality of alternative predicted 3D structures of the set of one or more molecules; and determining a respective alignment score for each of the plurality of alternative predicted 3D structures of the set of one or more molecules for the training step; and training the set of generative model parameters of the generative model to optimize the alignment objective.
    Type: Grant
    Filed: February 24, 2025
    Date of Patent: September 1, 2026
    Assignee: Genesis Molecular AI, Inc.
    Inventors: Maruan Al-Shedivat, Kenneth Knute Leidal, Arthur Deng, David Li-Bland
  • TRAINING GENERATIVE MACHINE LEARNING MODELS FOR 3D MOLECULAR STRUCTURE PREDICTION USING ALIGNMENT OBJECTIVES
    Publication number: 20250364081
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a generative model by a machine learning training technique using an alignment objective. In one aspect, a method comprises, at each of a sequence of training steps: obtaining data characterizing a set of one or more molecules for the training step; processing, by the generative model, the data characterizing the set of one or more molecules to generate a plurality of alternative predicted 3D structures of the set of one or more molecules; and determining a respective alignment score for each of the plurality of alternative predicted 3D structures of the set of one or more molecules for the training step; and training the set of generative model parameters of the generative model to optimize the alignment objective.
    Type: Application
    Filed: February 24, 2025
    Publication date: November 27, 2025
    Inventors: Maruan Al-Shedivat, Kenneth Knute Leidal, Arthur Deng, David Li-Bland