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- 16 commits
- 14 files changed
- 2 contributors
Commits on Dec 8, 2021
Commits on Dec 16, 2021
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Merge pull request #11 from msubedar/dnn2bnn
Adding new feature to create Bayesian deep neural network model from predefined deterministic model architecture i.e. drop-in replacements of Convolutional, Linear and LSTM layers to corresponding Bayesian layers (configured by 'const_bnn_prior_parameters' to set the prior parameters and sampling estimator - Reparameterization or Flipout method). This PR will enable seamless conversion of existing topology of larger models to Bayesian models for extending towards uncertainty-aware applications.
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update the posterior variational param init value
Signed-off-by: Ranganath Krishnan <ranganath.krishnan@intel.com>
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remove duplicate kl_loss definition in Conv1dReparameterization layer
Signed-off-by: Ranganath Krishnan <ranganath.krishnan@intel.com>
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include kl_loss() function in Convolutional flipout layers,
to compute kl when 'return_kl' flag is set to False. Fix for issue#12. Signed-off-by: Ranganath Krishnan <ranganath.krishnan@intel.com>
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Commits on Jan 13, 2022
Commits on Jan 17, 2022
Commits on Jan 18, 2022
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