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Just a heads up that this will be an annoying wrapper to make, since it involves a lot of tedious calculations from the wrapper side (sorry about that). It will probably be fine to postpone this for a while, since if Python users really want to try GRF for survival data they can always estimate Inverse Probability of Censoring Weights with a survival forest and pass those as sample_weights to a causal forest.
implemented but not yet released in grf
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