Accelerating GAN training using highly parallel hardware on public cloud

no code implementations • 8 Nov 2021 • Renato Cardoso, Dejan Golubovic, Ignacio Peluaga Lozada, Ricardo Rocha, João Fernandes, Sofia Vallecorsa

With the increasing number of Machine and Deep Learning applications in High Energy Physics, easy access to dedicated infrastructure represents a requirement for fast and efficient R&D.

Generative Adversarial Network

Asteroseismic modelling of solar-type stars: A deeper look at the treatment of initial helium abundance

no code implementations • 15 Oct 2020 • Benard Nsamba, Nuno Moedas, Tiago L. Campante, Margarida S. Cunha, Antonio García Hernández, Juan C. Suárez, Mário J. P. F. G. Monteiro, João Fernandes, Chen Jiang, Babatunde Akinsanmi

Adopting 35 low-mass, solar-type stars with multi-year Kepler photometry from the asteroseismic "LEGACY" sample, we explore the systematic uncertainties on the inferred stellar parameters (i. e., radius, mass, and age) arising from the treatment of the initial helium abundance in stellar model grids .

Solar and Stellar Astrophysics