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Found 5 papers, 1 papers with code
Efficient Identification in Linear Structural Causal Models with Auxiliary Cutsets
We develop a a new polynomial-time algorithm for identification in linear Structural Causal Models that subsumes previous non-exponential identification methods when applied to direct effects, and unifies several disparate approaches to identification in linear systems.
Sequential Causal Imitation Learning with Unobserved Confounders
"Monkey see monkey do" is an age-old adage, referring to na\"ive imitation without a deep understanding of a system's underlying mechanics.
Causal Imitation Learning with Unobserved Confounders
One of the common ways children learn is by mimicking adults.
Efficient Identification in Linear Structural Causal Models with Instrumental Cutsets
Building on the literature of instrumental variables (IVs), a plethora of methods has been developed to identify causal effects in linear systems.
Identification and Model Testing in Linear Structural Equation Models using Auxiliary Variables
In this paper, we provide an algorithm for the identification of causal parameters in linear structural models that subsumes previous state-of-the-art methods.
