Inferpy

=======
InferPy is a high-level API for defining probabilistic models containing deep neural networks in Python and capable of running on top of
Edward and TensorFlow. InferPy’s API is strongly inspired by Keras and it has a focus on enabling flexible
data processing, easy-to-code probabilistic modeling, scalable inference and robust model validation.


Changes:
- Fixed some bugs related to posterior predictive computation.
- Small internal enhancement.


**Release Date**: 26/08/2019
**Further Information**: [Documentation](http://inferpy.readthedocs.io/)

=======
InferPy is a high-level API for defining probabilistic models containing deep neural networks in Python and capable of running on top of
Edward and TensorFlow. InferPy’s API is strongly inspired by Keras and it has a focus on enabling flexible
data processing, easy-to-code probabilistic modeling, scalable inference and robust model validation.


Changes:
- Updated requirements.
- New extra requirements: visualization, datasets.


**Release Date**: 08/08/2019
**Further Information**: [Documentation](http://inferpy.readthedocs.io/)

=======
InferPy is a high-level API for defining probabilistic models containing deep neural networks in Python and capable of running on top of
Edward and TensorFlow. InferPy’s API is strongly inspired by Keras and it has a focus on enabling flexible
data processing, easy-to-code probabilistic modeling, scalable inference and robust model validation.


Changes:
- API for prior, posterior, and posterior_predictive queries.
- GPU support.
- Small changes in code structure.
- Fixed compatibility issue with TFP 0.7.0.
- Documentation updated.
- Fixed some bugs.


**Release Date**: 04/07/2019
**Further Information**: [Documentation](http://inferpy.readthedocs.io/)

=======
InferPy is a high-level API for defining probabilistic models containing deep neural networks in Python and capable of running on top of
Edward and TensorFlow. InferPy’s API is strongly inspired by Keras and it has a focus on enabling flexible
data processing, easy-to-code probabilistic modeling, scalable inference and robust model validation.


Changes:
- Extensive re-design of the API.
- Compatible with TFP/Edward 2.
- Edward 1 is not further supported.


**Release Date**: 27/05/2019
**Further Information**: [Documentation](http://inferpy.readthedocs.io/)

========
InferPy is a high-level API for probabilistic modeling written in Python and capable of running on top of
Edward and TensorFlow. InferPy’s API is strongly inspired by Keras and it has a focus on enabling flexible
data processing, easy-to-code probabilistic modeling, scalable inference and robust model validation.


Changes:
- batch parameter in random variable definitions.
- Changes in documentation.
- Name reference to replicate constructs.
- Predefiend and custom parametrised models (inf.models.predefiend)
- Version flag moved to inferpy/\_\_init\_\_.py
- Fixed some bugs.

**Release Date**: 23/11/2018
**Further Information**: [Documentation](http://inferpy.readthedocs.io/)

========
InferPy is a high-level API for probabilistic modeling written in Python and capable of running on top of
Edward and TensorFlow. InferPy’s API is strongly inspired by Keras and it has a focus on enabling flexible
data processing, easy-to-code probabilistic modeling, scalable inference and robust model validation.


Changes:
- Fixed some bugs.
- matmul and dot operations support new input types (numpy, tensors, lists and InferPy variables).
- Extended documentation.
- Moved Qmodel module to inferences package.
- Multidimensional InferPy variables are now indexed in the same way than
numpy arrays (get_item operator).
- Auto-install dependencies fixed.


**Release Date**: 02/10/2018
**Further Information**: [Documentation](http://inferpy.readthedocs.io/)