The Fisher Information Metric is a statistic used to measure the difference between two probability distributions. It is named after the statistician Ronald Fisher, who first proposed it in 1936.
The Fisher Information Metric can be thought of as the difference between the Shannon and Kolmogorov statistics, and is often used to compare two probability distributions.
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