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pro vyhledávání: '"Vidhi Lalchand"'
Autor:
Vidhi Lalchand, Joseph Duris, Adi Hanuka, Zhen Zhang, Xiaobiao Huang, J. Shtalenkova, Daniel Ratner, Auralee Edelen, D. Kennedy
Publikováno v:
Physical Review Accelerators and Beams, Vol 24, Iss 7, p 072802 (2021)
High-dimensional optimization is a critical challenge for operating large-scale scientific facilities. We apply a physics-informed Gaussian process (GP) optimizer to tune a complex system. Typical GP models learn from past observations to make predic
Autor:
Alexander A. Aldrick, Vidhi Lalchand, Miguel Garcia-Ortegon, Alpha A. Lee, Ryan-Rhys Griffiths
Publikováno v:
Machine Learning: Science and Technology. 3:015004
Bayesian optimisation is a sample-efficient search methodology that holds great promise for accelerating drug and materials discovery programs. A frequently-overlooked modelling consideration in Bayesian optimisation strategies however, is the repres
Publikováno v:
Communications of the ACM. 56:76-85
The competitive nature of AT, the scarcity of expertise, and the vast profits potential, makes for a secretive community where implementation details are difficult to find.