Invention Grant
- Patent Title: Deep neural network system for similarity-based graph representations
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Application No.: US18087704Application Date: 2022-12-22
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Publication No.: US11983269B2Publication Date: 2024-05-14
- Inventor: Yujia Li , Chenjie Gu , Thomas Dullien , Oriol Vinyals , Pushmeet Kohli
- Applicant: DeepMind Technologies Limited
- Applicant Address: GB London
- Assignee: DeepMind Technologies Limited
- Current Assignee: DeepMind Technologies Limited
- Current Assignee Address: GB London
- Agency: Fish & Richardson P.C.
- Main IPC: G06F21/56
- IPC: G06F21/56 ; G06F16/901 ; G06F17/16 ; G06F18/22 ; G06F21/57 ; G06N3/04 ; G06V10/426 ; G06V10/82 ; G06V30/196

Abstract:
There is described a neural network system implemented by one or more computers for determining graph similarity. The neural network system comprises one or more neural networks configured to process an input graph to generate a node state representation vector for each node of the input graph and an edge representation vector for each edge of the input graph; and process the node state representation vectors and the edge representation vectors to generate a vector representation of the input graph. The neural network system further comprises one or more processors configured to: receive a first graph; receive a second graph; generate a vector representation of the first graph; generate a vector representation of the second graph; determine a similarity score for the first graph and the second graph based upon the vector representations of the first graph and the second graph.
Public/Granted literature
- US20230134742A1 DEEP NEURAL NETWORK SYSTEM FOR SIMILARITY-BASED GRAPH REPRESENTATIONS Public/Granted day:2023-05-04
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