Gaussian adaptation refers to a statistical technique or a family of methods used to adaptively modify a Gaussian distribution based on observed data. This concept is often applied in various fields, including machine learning, statistical inference, and signal processing. Here are a few contexts where Gaussian adaptation is relevant: 1. **Probabilistic Models**: In Bayesian statistics, Gaussian adaptation can be used to update the parameters of a Gaussian distribution as new data becomes available.
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