0.2.2

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 bug #110 when defining a Poisson.

Release Date: 31/01/2019
Further Information: Documentation

0.2.1

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 the documentation.
• Name reference to replicate constructs.
• Predefined and custom parametrized models (inf.models.predefiend)
• Version flag moved to inferpy/__init__.py
• Fixed some bugs.

Release Date: 23/11/2018
Further Information: Documentation

0.2.0

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

0.1.2

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:

• MetropolisHastings (MCMC) inference method
• Creation of empirical q variables
• dot operator
• indexation operator
• MultivariateNormalDiag distribution
• methods mean(), variance() and sddev() for random variables

Release Date: 3/08/2018
Further Information: Documentation

0.1.1

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 modelling, scalable inference and robust model validation.

Changes:

• Fixed some bugs
• Prediction and evaluation functionality
• Function inf.case_states allows lists of variables as input
• Simple output string for distributions
• Added inf.gather operation
• Transpose is allowed when using inf.matmul
• inf.case works inside a replicate construct
• ProbModel.copy()
• Code reorganization

Release Date: 21/06/2018
Further Information: Documentation

0.1.0

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 probablistic modelling, scalable inference and robust model validation.

Changes:

• Fixed some bugs
• Qmodel class
• New distributions: Gamma, Bernoulli, InverseGamma, Laplace
• inferpy.models.ALLOWED_VARS is a list with all the types of variables (i.e., distributions) allowed.
• infMethod argument in compile method
• inferpy.case function wrapping tensorflow.case
• Boolean operators
• Correlated samples from ProbModel

Release Date: 14/05/2018
Further Information: Documentation

0.0.3

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 probablistic modelling, scalable inference and robust model validation.

Changes:

• Fixed some bugs
• New distributions: Beta, Exponential, Uniform, Poisson, Categorical, Multinomial, Dirichlet
• Integration with pandas

Release Date: 25/03/2018
Further Information: Documentation

0.0.2

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 probablistic modelling, scalable inference and robust model validation.

Changes:

• Fixed some bugs
• RandomVariable base class
• Optional parameter for returning a Tensorflow object
• Latent variables
• Dependency between variables
• Definition of probabilistic models
• Inference with KLqp

Release Date: 02/03/2018
Further Information: Documentation, Pypi package

0.0.1

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 probablistic modelling, scalable inference and robust model validation.

This version includes the basic functionality:

• Normal distribution
• Replicate construct

Release Date: 09/02/2018
Further Information: Documentation