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Found 6 papers, 3 papers with code
Random Forests for Adaptive Nearest Neighbor Estimation of Information-Theoretic Quantities
Information-theoretic quantities, such as conditional entropy and mutual information, are critical data summaries for quantifying uncertainty.
Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep Networks
In particular, Forests dominate other methods in tabular data, that is, when the feature space is unstructured, so that the signal is invariant to a permutation of the feature indices.
High-dimensional and universally consistent k-sample tests
The evaluation included several popular independence statistics and covered a comprehensive set of simulations.
mvlearn: Multiview Machine Learning in Python
As data are generated more and more from multiple disparate sources, multiview data sets, where each sample has features in distinct views, have ballooned in recent years.
MANIFOLD FORESTS: CLOSING THE GAP ON NEURAL NETWORKS
In particular, DFs dominate other methods in tabular data, that is, when the feature space is unstructured, so that the signal is invariant to permuting feature indices.
