"While this research was motivated by the problem of elucidating cellular programs, we first had to develop a novel causal ...

They then went about the laborious, and utterly uncertain, task of gathering corroborating evidence for the theory and submitting it to the systematic attempts of other scientist to refute it. Def.: ...

Hence, it is desirable to obtain causal information from observational ... As IDA is supported by mathematical theory, we expect the results presented here to generalize to other problems.

Andrews, Isaiah, Nano Barahona, Matthew Gentzkow, Ashesh Rambachan, and Jesse M. Shapiro. "Causal Interpretation of Structural IV Estimands." NBER Working Paper ...

This courses introduces causal inference methods, primarily using probabilistic graphical models, to identify and estimate counterfactual quantities as functions of observational data. We will discuss ...

Bayesian statistics in contemporary data science signify a paradigm revolution in probabilistic argumentation that provides ...

While some attempts to give string theory predictive power are underway, many physicists are looking elsewhere. Whether in the form of loop quantum gravity, causal dynamical trangulation or ...