Effective resistances have a broad range of algorithmic implications.

Our focus in this paper is to solve causal inference problems using only observational data and (potentially partial) knowledge on the causal graph of the underlying structural causal model (SCM).

To design an efficient intervention, decision-makers need not only to estimate the total effect of the intervention, but also understand the underlying causal mechanisms driving this effect.

As a result, these and other large conferences must rely on automated systems to decide what members of the impaneled reviewer pool will review each paper.