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US 2022/0101122 A1Published application
Energy-based variational autoencoders
AssigneeNVIDIA Corporation
InventorsArash VAHDAT, Karsten KREIS, Zhisheng XIAO, Jan KAUTZ
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AssigneeNVIDIA Corporation
InventorsArash VAHDAT, Karsten KREIS, Zhisheng XIAO, Jan KAUTZ
Estimating the term…
One embodiment of the present invention sets forth a technique for generating data using a generative model. The technique includes sampling from one or more distributions of one or more variables to generate a first set of values for the one or more variables, where the one or more distributions are used during operation of one or more portions of the generative model. The technique also includes applying one or more energy values generated via an energy-based model to the first set of values to produce a second set of values for the one or more variables. The technique further includes either outputting the set of second values as output data or performing one or more operations based on the second set of values to generate output data.
A computer-implemented method for generating images using a variational autoencoder, the method comprising:
A computer-implemented method for generating data using a generative model, the method comprising:
One or more non-transitory computer readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of:
Dependencies are inferred from the claim text.