Releases: PGM-Lab/InferPy
1.3.1
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:
- Documentation updated.
- Extras requirements modified: keyword
all
installs only CPU dependencies whileall-gpu
also those for GPUs are installed .
1.3.0
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:
- Integration with Bayesian Layers from TFP.
- Keras models can be defined inside InferPy models.
- Inference with MCMC.
- Documentation update.
- Fixed bugs #200, #201, #202.
Release Date: 12/02/2020
Further Information: Documentation
1.2.3
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:
- Bug detected at #195: false dependency is created between RVs which
are acenstors of a trainable layer. - Documentation updated.
Release Date: 18/10/2019
Further Information: Documentation
1.2.2
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:
- Hotfix at #193, dependency changed of
tensorflow-probability
from>=0.5.0,<0.1.0
to>=0.5.0,<0.8.0
.
Release Date: 10/10/2019
Further Information: Documentation
1.2.1
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:
- Function
inf.MixtureGaussian
encapsulatinged.MixtureSameFamily
. - Documentation updated.
Release Date: 19/09/2019
Further Information: Documentation
1.2.0
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:
- Data handling from memory and CSV files.
- Renamed inferpy.datasets to inferpy.data.
- Internal code enhancements.
- Documentation extended.
- Fixed some bugs.
Release Date: 29/08/2019
Further Information: Documentation
1.1.3
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 improvements.
Release Date: 26/08/2019
Further Information: Documentation
1.1.1
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
1.1.0
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
1.0.0
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