Patents by Inventor Jorg Bornschein

Jorg Bornschein 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).

  • Publication number: 20240119302
    Abstract: A method of automatically selecting a neural network from a plurality of computer-implemented candidate neural networks, each candidate neural network comprising at least an encoder neural network trained to encode an input value as a latent representation. The method comprises: obtaining a sequence of data items, each of the data items comprising an input value and a target value; and determining a respective score for each of the candidate neural networks, comprising evaluating the encoder neural network of the candidate neural network using a plurality of read-out heads. Each read-out head comprises parameters for predicting a target value from a latent representation of an input value of a data item encoded using the encoder neural network of the candidate neural network. The method further comprises selecting the neural network from the plurality of candidate neural networks using the respective scores.
    Type: Application
    Filed: September 27, 2023
    Publication date: April 11, 2024
    Inventors: Yazhe Li, Jorg Bornschein, Marcus Hutter
  • Patent number: 10860928
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating data items. One of the systems is a neural network system comprising a memory storing a plurality of template data items; one or more processors configured to select a memory address based upon a received input data item, and retrieve a template data item from the memory based upon the selected memory address; an encoder neural network configured to process the received input data item and the retrieved template data item to generate a latent variable representation; and a decoder neural network configured to process the retrieved template data item and the latent variable representation to generate an output data item.
    Type: Grant
    Filed: November 19, 2019
    Date of Patent: December 8, 2020
    Assignee: DeepMind Technologies Limited
    Inventors: Andriy Mnih, Daniel Zorn, Danilo Jimenez Rezende, Jorg Bornschein
  • Publication number: 20200090043
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating data items. One of the systems is a neural network system comprising a memory storing a plurality of template data items; one or more processors configured to select a memory address based upon a received input data item, and retrieve a template data item from the memory based upon the selected memory address; an encoder neural network configured to process the received input data item and the retrieved template data item to generate a latent variable representation; and a decoder neural network configured to process the retrieved template data item and the latent variable representation to generate an output data item.
    Type: Application
    Filed: November 19, 2019
    Publication date: March 19, 2020
    Inventors: Andriy Mnih, Daniel Zorn, Danilo Jimenez Rezende, Jorg Bornschein