The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Feb. 24, 2026
Filed:
Feb. 25, 2021
International Business Machines Corporation, Armonk, NY (US);
The Board of Trustees of the University of Illinois, Urbana, IL (US);
Yada Zhu, Irvington, NY (US);
Hanghang Tong, Champaign, IL (US);
Baoyu Jing, Urbana, IL (US);
Jinjun Xiong, Goldens Bridge, NY (US);
Nitin Gaur, Round Rock, TX (US);
Anna Wanda Topol, Clifton Park, NY (US);
International Business Machines Corporation, Armonk, NY (US);
The Board of Trustees of the University of Illinois, Urbana, IL (US);
Abstract
One or more machine learning models for a network of tensor time series can be provided. Co-evolving time series having multiple modes can be received. A tensor graph convolutional network can be trained, using the co-evolving time series and adjacency matrices associated with the multiple modes in the co-evolving time series, to generate node embeddings associated with a snapshot of the co-evolving time series at time t. A tensor recurrent neural network can be trained to generate temporal dynamics associated with the co-evolving time series based on the generated node embeddings. A neural network model can be trained to forecast a prediction for the co-evolving time series based on the generated node embeddings and the generated temporal dynamics. The tensor graph convolutional network, the tensor recurrent neural network and the neural network model can be trained jointly.