# How can Gröbner bases used to describe discrete probability?

[Cross post from here, figured this community may be more relevant]

I am working in the field of machine learning, and I have come across a few papers that show relationships between Gröbner bases and discrete probability. So I come here for help.

Can you please explain how can Gröbner bases used to describe discrete probability?

I have looked at Gröbner bases and I understand the general concepts (and used Maple to calculate a few examples). So it is the link that is missing for me.

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