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Constraining the 3HDM parameter space using active learning

Nipun Batra1,*, Baradhwaj Coleppa2,†, Akshat Khanna2,‡, Santosh Kumar Rai3,§, and Agnivo Sarkar3,∥

  • *Contact author: nipun.batra@iitgn.ac.in
  • †Contact author: baradhwaj@iitgn.ac.in
  • ‡Contact author: khanna_akshat@iitgn.ac.in
  • §Contact author: skrai@hri.res.in
  • ∥Contact author: agnivosarkar@hri.res.in

Surveying the complex three Higgs doublet model with Machine Learning

Rafael Boto, João A. C. Matos, Jorge C. Romão, and João P. Silva

J. High Energ. Phys. 2026 182 (2026)

Machine Learning in the 2HDM2S model for Dark Matter

Rafael Boto, T. P. Rebelo, Jorge C. Romão, and João P. Silva

J. High Energ. Phys. 2026 195 (2026)

ILC phenomenology of the $$Z_3$$ symmetric type-Z three Higgs doublet model

Baradhwaj Coleppa, Akshat Khanna, and Gokul B. Krishna

Eur. Phys. J. C 86 260 (2026)

A Renormalizable Neutrino Mass Model With (Z2 × Z4)⋊Z2(II) Symmetry

V. V. Vien, H. N. Long, T. D. Tham, and Burak Bilki

Advances in High Energy Physics 2026 2994666 (2026)

Unearthing large pseudoscalar Yukawa couplings with machine learning

Fernando Abreu de Souza, Rafael Boto, Miguel Crispim Romão, Pedro N. Figueiredo, Jorge C. Romão, and João P. Silva

J. High Energ. Phys. 2025 268 (2025)

Inert dark matter in three Higgs doublet model: a blind spot narrative

Amit Dutta Banik, Tapoja Jha, and Eija Tanskanen

J. Cosmol. Astropart. Phys. 2025 054 (2025)

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