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US Patent 10354015 Processing text sequences using neural networks

Patent 10354015 was granted and assigned to Deepmind Technologies Limited on July, 2019 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
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Patent attributes

Patent Applicant
Deepmind Technologies Limited
Deepmind Technologies Limited
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Current Assignee
Deepmind Technologies Limited
Deepmind Technologies Limited
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
103540150
Patent Inventor Names
Karen Simonyan0
Lasse Espeholt0
Nal Emmerich Kalchbrenner0
Date of Patent
July 16, 2019
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Patent Application Number
160329710
Date Filed
July 11, 2018
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Patent Citations
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US Patent 10049106 Natural language generation through character-based recurrent neural networks with finite-state prior knowledge
Patent Citations Received
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US Patent 12063226 Graph-based multi-staged attack detection in the context of an attack framework
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US Patent 11862146 Multistream acoustic models with dilations
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US Patent 11869530 Generating audio using neural networks
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US Patent 11875131 Zero-shot cross-lingual transfer learning
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US Patent 11948086 Accelerated embedding layer computations
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US Patent 11948066 Processing sequences using convolutional neural networks
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US Patent 11956253 Ranking cybersecurity alerts from multiple sources using machine learning
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US Patent 10586531 Speech recognition using convolutional neural networks
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Patent Primary Examiner
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Susan I McFadden
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Patent abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for neural machine translation. In one aspect, a system is configured to receive an input sequence of source embeddings representing a source sequence of words in a source natural language and to generate an output sequence of target embeddings representing a target sequence of words that is a translation of the source sequence into a target natural language, the system comprising: a dilated convolutional neural network configured to process the input sequence of source embeddings to generate an encoded representation of the source sequence, and a masked dilated convolutional neural network configured to process the encoded representation of the source sequence to generate the output sequence of target embeddings.

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