Invention Application
- Patent Title: COMMITTED INFORMATION RATE VARIATIONAL AUTOENCODERS
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Application No.: US16586014Application Date: 2019-09-27
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Publication No.: US20200104640A1Publication Date: 2020-04-02
- Inventor: Benjamin Poole , Aaron Gerard Antonius van den Oord , Ali Razavi-Nematollahi , Oriol Vinyals
- Applicant: DeepMind Technologies Limited
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06N7/00 ; G06N3/04 ; G06N3/08

Abstract:
A variational autoencoder (VAE) neural network system, comprising an encoder neural network to encode an input data item to define a posterior distribution for a set of latent variables, and a decoder neural network to generate an output data item representing values of a set of latent variables sampled from the posterior distribution. The system is configured for training with an objective function including a term dependent on a difference between the posterior distribution and a prior distribution. The prior and posterior distributions are arranged so that they cannot be matched to one another. The VAE system may be used for compressing and decompressing data.
Public/Granted literature
- US10671889B2 Committed information rate variational autoencoders Public/Granted day:2020-06-02
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