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A new technique for causal inference that can sometimes learn more than a randomized controlled trial.

The first known algorithm for causal discovery under latent class counfounding.

Domain expertise bias creates paradoxes in causality and covariate shift methods. We show these are the same as paradoxes in social choice theory.

We introduce mutation profiles as a way to capture time-dependent information in the repeat region of a genome and demonstrate the ability of mutation profiles to predict cancer-type from non-tumor DNA.

We use Prony’s method to solve the $k$-MixIID problem, which gives improved sample and time complexity via a new stability analysis.

We demonstrate that amplification processes lead to biases in TCGA data.