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The codes in this repository implement algorithms described in the paper "An Iterative Closest Points Approach to Neural Generative Models", which is also included in the repository. The algorithms train neural networks to learn mappings between distributions.
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DistributionMapper
PythonModule
SmallTensorflowExample
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README.txt

README.txt

The codes in this repository implement algorithms described in the paper "An Iterative Closest Points Approach to Neural Generative Models" (https://arxiv.org/abs/1711.06562). The algorithms train neural networks to learn mappings between distributions.

The folder "PythonModule" contains a Visual Studio solution to build a Python module that can be used to perform the matching, which is described in the paper. The example in the folder "SmallTensorflowExample" illustrates the use of the module.
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