The Higgs potential is vital to understand the electroweak symmetry breaking mechanism, and probing the Higgs self-interaction is arguably one of the most important physics targets at current and upcoming collider experiments. In particular, the triple Higgs coupling may be accessible at the HL-LHC by combining results in multiple channels, which motivates to study all possible decay modes for the double Higgs production. In this talk, we revisit the double Higgs production at the HL-LHC, and focus on the performance of various neural network architectures with different input features: low-level (four momenta), high-level (kinematic variables) and image-based.