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Commits on Jan 24, 2018

• Simplify VAE examples

  fchollet

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  10b46cb

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Commits on Nov 8, 2017

• Basic style fixes in example docstrings

  fchollet

  committed
  ce4947c

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Commits on Aug 29, 2017

• Change in variational autoencoder example to resolve issue keras-team#6373 (keras-team#7764)

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  dhaval067

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  fchollet

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Commits on Aug 23, 2017

• Remove requirement that batch_size divides len(x_train) in Variational Autoencoders examples. (keras-team#7716)

  

  danielegrattarola

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  fchollet

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Commits on Jun 26, 2017

• unify coding style (keras-team#7129)

  

  vwrs

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  fchollet

  committed
  a85263f

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Commits on Apr 11, 2017

• Switch variational examples to new API.

  fchollet

  committed
  4aa4162

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Commits on Mar 15, 2017

• using .add_loss in custom layer for VAE example

  Spotlight0xff

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  e848463

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Commits on Feb 28, 2017

• Updated VAE examples (MLP and ConvNet) to the new API (keras-team#5552)

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  Spotlight0xff

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  fchollet

  committed
  4e50446

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Commits on Feb 15, 2017

• Integration tests passing.

  fchollet

  committed
  10bfb1c

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Commits on Jan 13, 2017

• Convert "dim_ordering" to "data_format".

  fchollet

  committed
  5adce52

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Commits on Jan 11, 2017

• PEP8 fixes in examples.

  fchollet

  committed
  309f586

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Commits on Nov 23, 2016

• fixed variational autoencoder visualization for Gaussian latent space (keras-team#4423)

  

  Dontloo

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  fchollet

  committed
  88f3b3f

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Commits on Nov 2, 2016

• changed VAE sampling variance to 1 (keras-team#4211)

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  thangbui

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  fchollet

  committed
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Commits on Sep 30, 2016

• Make deconv VAE compatible with both dim orderings

  fchollet

  committed
  8fab33c

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Commits on Sep 29, 2016

• Keras is TF first. Fix TH first example (keras-team#3914)

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  EderSantana

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  fchollet

  committed
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Commits on Sep 28, 2016

• Bypass shape inference in deconv2d and use the output shape provided by the user (keras-team#3838)

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  Thomas Boquet

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  fchollet

  committed
  51c85dd

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Commits on Jul 25, 2016

• Style fixes

  fchollet

  committed
  f6bcaff

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• Implemented transposed (de-) convolutions into Keras (keras-team#3251)

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  yaringal

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  fchollet

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