[GitHub] thomelane opened a new issue #12932: Probability Distributions Support

[GitBox <gi...@apache.org>]

thomelane opened a new issue #12932: Probability Distributions Support
URL: https://github.com/apache/incubator-mxnet/issues/12932
 
 
   ## Probability Distributions Support
   
   Would be great to have out-of-the-box support for distributions, similar to functionality provided by [TensorFlow Probability](https://www.tensorflow.org/probability) and [PyTorch Distributions](https://pytorch.org/docs/stable/distributions.html). My current use case is for Reinforcement Learning algorithms that learn stochastic action policies (i.e. learn parameters of a distribution from which actions are sampled), and I update these parameters using the likelihood.
   
   MXNet would ideally have methods on each type of distribution for calculating:
   
   * probability density,
   * log probability of a data sample given the distribution,
   * entropy of distribution,
   * kl divergence of distribution with another distribution,
   * sampling from distribution (mostly already implemented).
   
   And would support a variety of distributions including:
   
   * Categorical
   * MultivariateNormal
   * Bernoulli
   * Beta
   * Dirichlet
   * Exponential
   * Gamma
   * Poisson
   * Uniform
   
   [MXFusion](https://github.com/amzn/MXFusion) is a related project but doesn't have the functionality mentioned above. And it would be ideal to have this as a submodule of the MXNet package.

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