Dismantling complex networks based on higher-order graph neural network

Although existing research has confirmed the importance of higher-order structures in identifying key nodes within networks, the challenge remains on how to effectively integrate different types of higher-order information to precisely locate nodes that may be inconspicuous in lower-order structures but play a crucial role in higher-order interactions. To address this challenge, this paper proposes a general Higher-order Graph Neural Network representation learning framework (HoGNN) that can fle