Truncated Matrix Power Iteration for Differentiable DAG Learning

Neural Information Processing Systems 

Recovering underlying Directed Acyclic Graph (DAG) structures from observational data is highly challenging due to the combinatorial nature of the DAGconstrained optimization problem.

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