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Higgs boson pair production is well known to probe the structure of theelectroweak symmetry breaking sector. We illustrate using the gluon-fusionprocess $pp \to H \to h h \to (b\bar b) (b\bar b)$ in the framework oftwo-Higgs-doublet models and how the machine learning approach (three-streamconvolutional neural network) can substantially improve the signal-backgrounddiscrimination and thus improves the sensitivity coverage of the relevantparameter space. We show that such $gg \to hh \to b \bar b b\bar b$ process canfurther probe the currently allowed parameter space by HiggsSignals andHiggsBounds at the HL-LHC. The results for Types I to IV are shown.

Sensitivity on Two-Higgs-Doublet Models from Higgs-Pair Production via $b\bar{b}b\bar{b}$ Final State