InferPy is an open-source library for deep probabilistic modeling written in Python and running on top of Edward 2 and Tensorflow. Other existing probabilistic programming languages possess the drawback that they are difficult to use, especially when defining deep neural networks and probability distributions over multidimensional tensors. This means that their final goal of broadening the number of people able to code a machine learning application may not be fulfilled. InferPy tries to address these issues by defining a user-friendly API which trades-off model complexity with ease of use. In particular, this library allows users to: prototype hierarchical probabilistic models with a simple and user-friendly API inspired by Keras; define probabilistic models with complex constructs containing deep neural networks; create computationally efficient batched models without having to deal with complex tensor operations; and run seamlessly on CPUs and GPUs by relying on Tensorflow.
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Date: Tuesday, 28th of May 2019, 12:00-13:00
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Location: Manno, Galleria 1, 2nd floor, room G1-201