Patents by Inventor Francesco Sanna Passino

Francesco Sanna Passino 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: 20220377097
    Abstract: Disclosed are systems and methods for temporal link prediction based on (generalized) random dot product graphs (RDPGs), as well as applications of such temporal link prediction to network anomaly detection. In various embodiments, starting from a time series of adjacency matrices characterizing the evolution of the network, spectral embeddings and time-series models are used to predict estimated link probabilities for a future point in time, and the predicted link probabilities are compared against observed links to identify anomalous behavior. In some embodiments, element-wise independent models are used in the prediction to take network dynamics into account at the granularity of individual nodes or edges.
    Type: Application
    Filed: July 20, 2022
    Publication date: November 24, 2022
    Inventors: Anna Swanson BERTIGER, Francesco SANNA PASSINO, Joshua NEIL
  • Patent number: 11418526
    Abstract: Disclosed are systems and methods for temporal link prediction based on (generalized) random dot product graphs (RDPGs), as well as applications of such temporal link prediction to network anomaly detection. In various embodiments, starting from a time series of adjacency matrices characterizing the evolution of the network, spectral embeddings and time-series models are used to predict estimated link probabilities for a future point in time, and the predicted link probabilities are compared against observed links to identify anomalous behavior. In some embodiments, element-wise independent models are used in the prediction to take network dynamics into account at the granularity of individual nodes or edges.
    Type: Grant
    Filed: May 31, 2020
    Date of Patent: August 16, 2022
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Anna Swanson Bertiger, Francesco Sanna Passino, Joshua Neil
  • Publication number: 20210194907
    Abstract: Disclosed are systems and methods for temporal link prediction based on (generalized) random dot product graphs (RDPGs), as well as applications of such temporal link prediction to network anomaly detection. In various embodiments, starting from a time series of adjacency matrices characterizing the evolution of the network, spectral embeddings and time-series models are used to predict estimated link probabilities for a future point in time, and the predicted link probabilities are compared against observed links to identify anomalous behavior. In some embodiments, element-wise independent models are used in the prediction to take network dynamics into account at the granularity of individual nodes or edges.
    Type: Application
    Filed: May 31, 2020
    Publication date: June 24, 2021
    Inventors: Anna Swanson Bertiger, Francesco Sanna Passino, Joshua Neil