ProvablyEfficientNeuralEstimationofStructural EquationModel: AnAdversarialApproach

Structural equation models (SEMs) are widely used in sciences, ranging from economics topsychology,touncovercausal relationships underlying acomplex system under consideration and estimate structural parameters of interest. We study estimation in a class of generalized SEMs where the object of interest is defined as the solution to a linear operator equation.