Source: Program. Conference titles: CLAF/ICTP-SAIFR Latin-American Astroparticle Physics School. Unidade: IFSC
Subjects: APRENDIZADO COMPUTACIONAL, FÍSICA COMPUTACIONAL, ASTROFÍSICA, MÉTODO DE MONTE CARLO
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RABELO, Eduardo Fonseca. Mass composition classification of extensive air showers at CTAO via Monte Carlo simulations and machine learning. 2025, Anais.. São Paulo: International Centre for Theoretical Physics, South American Institute for Fundamental Research - ICTP-SAIFR, 2025. Disponível em: https://repositorio.usp.br/directbitstream/378447b6-af38-41a1-9694-e8251cd9c0a7/3266949.pdf. Acesso em: 08 out. 2025.APA
Rabelo, E. F. (2025). Mass composition classification of extensive air showers at CTAO via Monte Carlo simulations and machine learning. In Program. São Paulo: International Centre for Theoretical Physics, South American Institute for Fundamental Research - ICTP-SAIFR. Recuperado de https://repositorio.usp.br/directbitstream/378447b6-af38-41a1-9694-e8251cd9c0a7/3266949.pdfNLM
Rabelo EF. Mass composition classification of extensive air showers at CTAO via Monte Carlo simulations and machine learning [Internet]. Program. 2025 ;[citado 2025 out. 08 ] Available from: https://repositorio.usp.br/directbitstream/378447b6-af38-41a1-9694-e8251cd9c0a7/3266949.pdfVancouver
Rabelo EF. Mass composition classification of extensive air showers at CTAO via Monte Carlo simulations and machine learning [Internet]. Program. 2025 ;[citado 2025 out. 08 ] Available from: https://repositorio.usp.br/directbitstream/378447b6-af38-41a1-9694-e8251cd9c0a7/3266949.pdf
