A machine learning framework, equipped with a unitary Koopman structure, is designed to reconstruct Hamiltonian systems using either noise-perturbed or partially observational data. This framework can ...

Abstract: In the past couple of decades, significant research efforts are devoted to the prediction of software bugs. However, most existing work in this domain treats all bugs the same, which is not ...

Abstract: Neural code models (NCMs) have demonstrated extraordinary capabilities in code intelligence tasks. Meanwhile, the security of NCMs and NCMs-based systems has garnered increasing attention.