To extend Xenovert to handle high-dimensional input distributions, we can implement an N-dimensional Xenovert. This would involve creating a tree structure with multiple branches, each corresponding to a different feature or dimension of the input space. By expanding the binary tree structure to accommodate the additional dimensions, Xenovert can effectively partition the high-dimensional input space into intervals and adapt to changes in distribution across all dimensions. This extension would allow Xenovert to maintain its adaptive capabilities and uniform division of the input space in scenarios with high-dimensional data.