| − | Although NIS took the lead in proposing a scheme to optimize EI to identify causal emergence in data, this method has some shortcomings: the author divides the optimization process into two stages, but does not truly maximize the EI, that is, Equation {{EquationNote|1}}. Therefore, [[Yang Mingzhe]] et al. <ref name=":6" /> further improved this method and proposed the [[NIS+]] scheme. By introducing reverse dynamics and [[reweighting technique]], the original maximization of EI is transformed into maximizing its variational lower bound. This is achieved using [[variational inequality]], enabling the direct optimization of the objective function. | + | Although NIS took the lead in proposing a scheme to optimize EI to identify causal emergence in data, this method has some shortcomings: the author divides the optimization process into two stages, but does not truly maximize the EI, that is, Equation {{EquationNote|1}}. Therefore, Yang et al. <ref name=":6" /> further improved this method and proposed the [[NIS+]] scheme. By introducing reverse dynamics and [[reweighting technique]], the original maximization of EI is transformed into maximizing its variational lower bound. This is achieved using [[variational inequality]], enabling the direct optimization of the objective function. |