首页|Study Data from Massachusetts Institute of Technology Update Knowledge of Machin e Learning (Florah: a Generative Model for Halo Assembly Histories)
Study Data from Massachusetts Institute of Technology Update Knowledge of Machin e Learning (Florah: a Generative Model for Halo Assembly Histories)
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2024 OCT 08 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Investigators discuss new findings in Machine Lea rning. According to news reporting from Cam-bridge, Massachusetts, by NewsRx jour nalists, research stated, "The mass assembly history (MAH) of dark matter haloes plays a crucial role in shaping the formation and evolution of galaxies. MAHs are used extensively in semi-analytic and empirical models of galaxy formation, y et current analytic methods to generate them are inaccurate and unable to captur e their relationship with the halo internal structure and large-scale environmen t." Funders for this research include Center for Computational Astrophysics at the F latiron Institute, Simons Foundation, National Science Foundation (NSF), NASA Po stdoctoral Program (NPP) at NASA Goddard Space Flight Center, Gauss Centre for S upercomputing e.V., Partnership for Advanced Supercomputing in Europe (PRACE).
CambridgeMassachusettsUnited StatesNorth and Central AmericaCyborgsDark MatterEmerging TechnologiesMachine LearningPhysicsMassachusetts Institute of Technology
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