Observation of the H -> WW* production by Vector Boson Fusion in 13 TeV $pp$ collisions with the ATLAS detector at the LHC

After the Higgs boson discovery at the LHC in 2012, it is now of great importance to measure the properties of the Higgs boson precisely to further understand its nature. The study of H -> WW* decays in the VBF production mode is particularly interesting, as it provides crucial measurements on the Higgs couplings to gauge bosons. The VBF process is characterized by two energetic jets along the beam axis and in opposite hemispheres. Due to large background contributions in events with two jets, machine learning techniques are used to exploit the VBF signature and to extract the signal most efficiently. In this presentation, I will discuss the improved analysis strategies, that lead to the first observation of the VBF, H -> WW* process and new measurements of the VBF production cross-section with the full Run 2 dataset, with special emphasis on the newly introduced Deep Learning Neural Network. This analysis provides an important baseline for future measurements of Simplified Template Cross-Sections (STXS) and other combined measurements in the Higgs sector.