Commits · f78f765f14a2598d659a8e48a934cd913865ff2b · Lucas Miranda / deepOF · GitLab

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Jul 03, 2020
- Implemented weight saving callback in model_training.py · f78f765f
  Lucas Miranda authored 4 years ago
  
  f78f765f
- Implemented weight saving callback in model_training.py · b834f5e5
  Lucas Miranda authored 4 years ago
  
  b834f5e5
Jul 01, 2020
- Implemented weight saving callback in model_training.py · f851531e
  Lucas Miranda authored 4 years ago
  
  f851531e
- Implemented weight saving callback in model_training.py · 9324194c
  Lucas Miranda authored 4 years ago
  
  9324194c
- Implemented weight saving callback in model_training.py · 31c3fc01
  Lucas Miranda authored 4 years ago
  
  31c3fc01
- Implemented weight saving callback in model_training.py · 5c4515b1
  Lucas Miranda authored 4 years ago
  
  5c4515b1
Jun 25, 2020
- Implemented weight saving callback in model_training.py · 672a2925
  Lucas Miranda authored 4 years ago
  
  672a2925
- Implemented weight saving callback in model_training.py · ed3b7821
  Lucas Miranda authored 4 years ago
  
  ed3b7821
Jun 18, 2020
- Implemented weight saving callback in model_training.py · a7365146
  Lucas Miranda authored 4 years ago
  
  a7365146
Jun 17, 2020
- Implemented weight saving callback in model_training.py · d10f27e4
  Lucas Miranda authored 4 years ago
  
  d10f27e4
- Implemented weight saving callback in model_training.py · 9d816a3c
  Lucas Miranda authored 4 years ago
  
  9d816a3c
- Reduced latent space dimensionality · 6981d1bc
  Lucas Miranda authored 4 years ago
  
  6981d1bc
Jun 16, 2020
- Fixed bug in preprocess.py · cec5db60
  Lucas Miranda authored 4 years ago
  
  cec5db60
Jun 15, 2020
- Updated hyperparameter_tuning.py to use the latest version of hypermodels.py · a7d35d3a
  Lucas Miranda authored 4 years ago
  
  a7d35d3a
- Updated hyperparameter_tuning.py to use the latest version of hypermodels.py · 93397d23
  Lucas Miranda authored 4 years ago
  
  93397d23
Jun 11, 2020
- Updated GMVAE and AE hypermodels for hyperparameter tuning in hypermodels.py · 1850e500
  Lucas Miranda authored 4 years ago
  
  1850e500
- Updated GMVAE and AE hypermodels for hyperparameter tuning in hypermodels.py · 49602467
  Lucas Miranda authored 4 years ago
  
  49602467
- Unified all VAE variants in a single model with different settings · ae817e08
  Lucas Miranda authored 4 years ago
  
  ae817e08
- Unified all VAE variants in a single model with different settings · c9ffecb6
  Lucas Miranda authored 4 years ago
  
  c9ffecb6
- Implemented deep clustering using a SEQ_2_SEQ_GMVAEP model · 31e69ef9
  Lucas Miranda authored 4 years ago
  
  31e69ef9
Jun 10, 2020
- Changed full model for diagonal model in all variational implementations in models.py · 1fe8e4b5
  Lucas Miranda authored 4 years ago
  
  1fe8e4b5
- Changed full model for diagonal model in all variational implementations in models.py · 5679171a
  Lucas Miranda authored 4 years ago
  
  5679171a
- Changed full model for diagonal model in all variational implementations in models.py · 75b256cf
  Lucas Miranda authored 4 years ago
  
  75b256cf
- Changed full model for diagonal model in all variational implementations in models.py · 4f79350b
  Lucas Miranda authored 4 years ago
  
  4f79350b
- Changed full model for diagonal model in all variational implementations in models.py · a52e96d8
  Lucas Miranda authored 4 years ago
  
  a52e96d8
- Changed full model for diagonal model in all variational implementations in models.py · 35822d92
  Lucas Miranda authored 4 years ago
  
  35822d92
- Changed full model for diagonal model in all variational implementations in models.py · 2761524a
  Lucas Miranda authored 4 years ago
  
  2761524a
- Changed full model for diagonal model in all variational implementations in models.py · 8aa85b4e
  Lucas Miranda authored 4 years ago
  
  8aa85b4e
- Changed full model for diagonal model in all variational implementations in models.py · b3941ccf
  Lucas Miranda authored 4 years ago
  
  b3941ccf
Jun 09, 2020
- Implemented version of SEQ_2_SEQ VAE based on tensorflow_probability, and... · 6cc67976
  Lucas Miranda authored 4 years ago
  
  Implemented version of SEQ_2_SEQ VAE based on tensorflow_probability, and SEQ_2_SEQ_GMVAE draft using tensorflow_probability
  6cc67976
- Implemented version of SEQ_2_SEQ VAE based on tensorflow_probability · d2096481
  Lucas Miranda authored 4 years ago
  
  d2096481
- Implemented version of SEQ_2_SEQ VAE based on tensorflow_probability · b99b3ace
  Lucas Miranda authored 4 years ago
  
  b99b3ace
Jun 08, 2020
- Instanciated a mean and a variance for each component, and the categorical... · b1862ad9
  Lucas Miranda authored 4 years ago
  
  Instanciated a mean and a variance for each component, and the categorical prior as a Dense layer with a softmax activation
  b1862ad9
- Instanciated a mean and a variance for each component, and the categorical... · ce80ff28
  Lucas Miranda authored 4 years ago
  
  Instanciated a mean and a variance for each component, and the categorical prior as a Dense layer with a softmax activation
  ce80ff28
Jun 07, 2020
- Instanciated a mean and a variance for each component, and the categorical... · 226b9801
  Lucas Miranda authored 4 years ago
  
  Instanciated a mean and a variance for each component, and the categorical prior as a Dense layer with a softmax activation
  226b9801
- Instanciated a mean and a variance for each component, and the categorical... · 7b86681d
  Lucas Miranda authored 4 years ago
  
  Instanciated a mean and a variance for each component, and the categorical prior as a Dense layer with a softmax activation
  7b86681d
Jun 06, 2020
- Initialised number of components in SEQ2SEQ_GMVAEP · dba020ba
  Lucas Miranda authored 4 years ago
  
  dba020ba
Jun 05, 2020
- Drafted GMVAEP model implementation in models.py · 0d43d1e7
  Lucas Miranda authored 4 years ago
  
  0d43d1e7
- Implemented KL and MMD warmup on SEQ2SEQ_VAEP in models.py · 442ed01b
  Lucas Miranda authored 4 years ago
  
  442ed01b
- Implemented KL and MMD warmup on SEQ2SEQ_VAEP in models.py · a3a6bdcb
  Lucas Miranda authored 4 years ago
  
  a3a6bdcb