A Nonstationary Soft Partitioned Gaussian Process Model via Random Spanning Trees

There has been a long-standing challenge in developing locally stationary Gaussian process models concerning how to obtain flexible partitions and make predictions near boundaries. In this work, we develop a new class of locally stationary stochastic processes, where local partitions are modeled by...

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