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Found 3 papers, 1 papers with code
Solving optimal stopping problems with Deep Q-Learning
We propose a reinforcement learning (RL) approach to model optimal exercise strategies for option-type products.
Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression
Random Forest (Breiman, 2001) is a successful and widely used regression and classification algorithm.
On the Use of Random Forest for Two-Sample Testing
The developed tests are easy to use, require almost no tuning, and are applicable for any distribution on $\mathbb{R}^d$.
Methodology
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