Supervised ML techniques based on Distribution of Dependent Variable Are there are any supervised ML techniques that take into account the distribution of target variables? In Statistics, quantile regressions are a good way to model the data based on conditional distribution of dependent variables.
I am curious if there are any techniques in ML literature that would be a good choice for modeling based on conditional distribution of dependent variable data?

Yes, but be aware regression is also a machine learning method. What you're looking to learn more about are loss functions, and you want to use a quantile loss function. You can usually specify your own loss function. In sklearn for example, you might have a loss parameter for your estimator, such as in sgdregressor.
See here for more info Quantile regression: Loss function
