Patents by Inventor Daniel William BUSBRIDGE

Daniel William BUSBRIDGE 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).

  • Patent number: 11321363
    Abstract: A graphical classification method for classifying graphical structures, said graphical structures comprising nodes defined by feature vectors and having relations between the nodes. The method includes representing the feature vectors and relations as a first graphical representation. The method also includes mapping said first graphical representation into a second graphical representation wherein the mapping comprises using an attention mechanism, said attention mechanism establishes the importance of specific feature vectors dependent on their neighbourhood and the relations between the feature vectors, said mapping transforming the feature vectors of the first graphical representation to transformed feature vectors in the second graphical representation. The method also includes combining the transformed feature vectors to obtain a third combined representation said third combined representation being an indication of the classification of the graphical structure.
    Type: Grant
    Filed: April 4, 2019
    Date of Patent: May 3, 2022
    Assignee: Babylon Partners Limited
    Inventors: Daniel William Busbridge, Pietro Cavallo, Dane Grant Sherburn, Nils Yannick Hammerla
  • Publication number: 20210374517
    Abstract: Embodiments described herein allow predictions to be made for any continuous position by making use of a continuous position embedding based on previous observations. An encoder-decoder structure is described herein that allows effective predictions for any position without requiring predictions for intervening positions to be determined. This provides improvements in computational efficiency. Specific embodiments can be applied to predicting the number of events that are expected to occur at or by a given time. Embodiments can be adapted to make predict based on electronic health records, for instance, determining the likelihood of a particular health event occurring by a particular time.
    Type: Application
    Filed: May 27, 2020
    Publication date: December 2, 2021
    Inventors: Joseph Henri Theodore Enguehard, Daniel William Busbridge, Adam Bozson
  • Patent number: 10846616
    Abstract: A computer-implemented method includes a computing system having a database that stores multiple datasets and that accesses the database to perform operations on a first dataset to produce multiple second datasets. The system determines a relationship between the first dataset and each second dataset of the multiple second datasets. The system also determines a relationship between respective groups of the first dataset and determines a relationship between respective groups of each second dataset. The system generates summary objects based, in part, on the determined relationships between respective groups of the first and second datasets. The system includes a machine learning system that uses the respective summary objects to analyze the performed operations that produced the multiple second datasets. Based on the analyzed performed operations, the machine learning system generates a data analysis model that indicates sequences of operations for achieving particular desired data analysis outcomes.
    Type: Grant
    Filed: April 28, 2017
    Date of Patent: November 24, 2020
    Assignee: IQVIA Inc.
    Inventors: Daniel William Busbridge, Gwyn Rhys Jones, Peter Paul Riebel
  • Patent number: 10824949
    Abstract: A method of training a model, said model being adapted to map a first graphical data structure representation to a second graphical data structure representation, the first graphical data structure representation comprising nodes, with at least one of a plurality of relations between said nodes, the second graphical data structure representation comprising nodes, the mapping comprises using an attention mechanism, wherein said attention mechanism establishes the importance of specific nodes dependent on their neighbourhood and the relations between the nodes, wherein the mapping comprising using a projection kernel to map the nodes of the first graphical structure to nodes of an intermediate representation and using an attention kernel to enact the attention mechanism. The method includes receiving a training data set comprising an output layer and a corresponding input layer. The method also includes training the parameters of the projection kernel and the attention kernel using the training data set.
    Type: Grant
    Filed: April 4, 2019
    Date of Patent: November 3, 2020
    Assignee: Babylon Partners Limited
    Inventors: Daniel William Busbridge, Pietro Cavallo, Dane Grant Sherburn, Nils Yannick Hammerla
  • Patent number: 10824653
    Abstract: A computer implemented method for classifying molecular structures is provided. The method includes representing the elements and atoms in a molecular structure as nodes and the bonds as relations as a first graphical representation. The method also includes mapping said first graphical representation into a second graphical representation wherein the mapping comprises using an attention mechanism, said attention mechanism establishes the importance of specific feature vectors dependent on their neighbourhood and the relations between the feature vectors, said mapping transforming the feature vectors of the first graphical representation to transformed feature vectors in the second graphical representation. The method also includes combining the transformed feature vectors to obtain a third combined representation. The method also includes mapping said third combined representation to a feature vector indicating properties of the molecular structure.
    Type: Grant
    Filed: April 4, 2019
    Date of Patent: November 3, 2020
    Assignee: Babylon Partners Limited
    Inventors: Daniel William Busbridge, Pietro Cavallo, Dane Grant Sherburn, Nils Yannick Hammerla
  • Publication number: 20200104729
    Abstract: A method of training a model, said model being adapted to map a first graphical data structure representation to a second graphical data structure representation, the first graphical data structure representation comprising nodes, with at least one of a plurality of relations between said nodes, the second graphical data structure representation comprising nodes, the mapping comprises using an attention mechanism, wherein said attention mechanism establishes the importance of specific nodes dependent on their neighbourhood and the relations between the nodes, wherein the mapping comprising using a projection kernel to map the nodes of the first graphical structure to nodes of an intermediate representation and using an attention kernel to enact the attention mechanism. The method includes receiving a training data set comprising an output layer and a corresponding input layer. The method also includes training the parameters of the projection kernel and the attention kernel using the training data set.
    Type: Application
    Filed: April 4, 2019
    Publication date: April 2, 2020
    Inventors: Daniel William BUSBRIDGE, Pietro CAVALLO, Dane Grant SHERBURN, Nils Yannick HAMMERLA
  • Publication number: 20200104409
    Abstract: A method of mapping a first graphical data structure representation to a second graphical data structure representation, the first graphical data structure representation comprising nodes, with at least one of a plurality of relations between said nodes, the second graphical data structure representation comprising nodes, the mapping comprises using an attention mechanism, wherein said attention mechanism establishes the importance of specific nodes dependent on their neighbourhood and the relations between the nodes.
    Type: Application
    Filed: September 27, 2018
    Publication date: April 2, 2020
    Inventors: Daniel William BUSBRIDGE, Pietro CAVALLO, Dane Grant SHERBURN, Nils Yannick HAMMERLA
  • Publication number: 20200104312
    Abstract: A graphical classification method for classifying graphical structures, said graphical structures comprising nodes defined by feature vectors and having relations between the nodes. The method includes representing the feature vectors and relations as a first graphical representation. The method also includes mapping said first graphical representation into a second graphical representation wherein the mapping comprises using an attention mechanism, said attention mechanism establishes the importance of specific feature vectors dependent on their neighbourhood and the relations between the feature vectors, said mapping transforming the feature vectors of the first graphical representation to transformed feature vectors in the second graphical representation. The method also includes combining the transformed feature vectors to obtain a third combined representation said third combined representation being an indication of the classification of the graphical structure.
    Type: Application
    Filed: April 4, 2019
    Publication date: April 2, 2020
    Inventors: Daniel William BUSBRIDGE, Pietro CAVALLO, Dane Grant SHERBURN, Nils Yannick HAMMERLA
  • Publication number: 20200104311
    Abstract: A computer implemented method for classifying molecular structures is provided. The method includes representing the elements and atoms in a molecular structure as nodes and the bonds as relations as a first graphical representation. The method also includes mapping said first graphical representation into a second graphical representation wherein the mapping comprises using an attention mechanism, said attention mechanism establishes the importance of specific feature vectors dependent on their neighbourhood and the relations between the feature vectors, said mapping transforming the feature vectors of the first graphical representation to transformed feature vectors in the second graphical representation. The method also includes combining the transformed feature vectors to obtain a third combined representation. The method also includes mapping said third combined representation to a feature vector indicating properties of the molecular structure.
    Type: Application
    Filed: April 4, 2019
    Publication date: April 2, 2020
    Inventors: Daniel William BUSBRIDGE, Pietro CAVALLO, Dane Grant SHERBURN, Nils Yannick HAMMERLA
  • Patent number: 10599686
    Abstract: A method of mapping a first graphical data structure representation to a second graphical data structure representation, the first graphical data structure representation comprising nodes, with at least one of a plurality of relations between said nodes, the second graphical data structure representation comprising nodes, the mapping comprises using an attention mechanism, wherein said attention mechanism establishes the importance of specific nodes dependent on their neighbourhood and the relations between the nodes.
    Type: Grant
    Filed: September 27, 2018
    Date of Patent: March 24, 2020
    Assignee: Babylon Partners Limited
    Inventors: Daniel William Busbridge, Pietro Cavallo, Dane Grant Sherburn, Nils Yannick Hammerla
  • Publication number: 20190317955
    Abstract: Computer-implemented methods for determining missing content in a database are provided. The database may contain a plurality of known embedded sentences and their relationship to content. In one aspect, a method includes receiving new queries and generating new embedded sentences from said new queries. The method also includes determining whether the new embedded sentences are similar to known embedded sentences. The method also includes generating a message indicating that new embedded sentence is not linked to content. Systems are also provided.
    Type: Application
    Filed: April 19, 2019
    Publication date: October 17, 2019
    Inventors: Vitalii ZHELEZNIAK, Daniel William BUSBRIDGE, April Tuesday SHEN, Samuel Laurence SMITH, Nils HAMMERLA
  • Publication number: 20190155945
    Abstract: Computer-implemented methods for retrieving content in response to receiving a natural language query are provided. In one aspect, a method includes receiving a natural language query submitted by a user using a user interface, generating an embedded sentence from said query, determining a similarity between the embedded sentence derived from the received natural language query and embedded sentences from queries saved in a database comprising a fixed mapping of responses to saved queries expressed as the embedded sentences, retrieving a response for an embedded sentence determined to be similar to one of the saved queries, and providing the response to the user via the user interface. Systems are also provided.
    Type: Application
    Filed: August 27, 2018
    Publication date: May 23, 2019
    Inventors: Vitalii ZHELEZNIAK, Daniel William BUSBRIDGE, April Tuesday SHEN, Samuel Laurence SMITH, Nils HAMMERLA