Invention Publication
- Patent Title: DATA COMPRESSION USING INTEGER NEURAL NETWORKS
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Application No.: US18520975Application Date: 2023-11-28
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Publication No.: US20240104786A1Publication Date: 2024-03-28
- Inventor: Nicholas Johnston , Johannes Balle
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Main IPC: G06T9/00
- IPC: G06T9/00 ; G06F17/18 ; G06N3/045 ; G06N3/084

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for reliably performing data compression and data decompression across a wide variety of hardware and software platforms by using integer neural networks. In one aspect, there is provided a method for entropy encoding data which defines a sequence comprising a plurality of components, the method comprising: for each component of the plurality of components: processing an input comprising: (i) a respective integer representation of each of one or more components of the data which precede the component in the sequence, (ii) an integer representation of one or more respective latent variables characterizing the data, or (iii) both, using an integer neural network to generate data defining a probability distribution over the predetermined set of possible code symbols for the component of the data.
Public/Granted literature
- US12154304B2 Data compression using integer neural networks Public/Granted day:2024-11-26
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