[D] Approximating non-Function Mappings with Mixture Density Networks

Hey everyone, I wrote a short blog post on approximating non-function, multi valued x->y mappings. In my opinion, understanding why and how to use Mixture Density Networks is a great exercise for all researchers and practitioners. Its very common that real world processes have multiple outcomes based on some random sampling; and naive neural networks will simply learn the geometric mean of all y for a given x.

Check out the blog post in more detail - hope you enjoy …

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