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pro vyhledávání: '"Smaldone, Anthony M."'
Autor:
Smaldone, Anthony M., Shee, Yu, Kyro, Gregory W., Xu, Chuzhi, Vu, Nam P., Dutta, Rishab, Farag, Marwa H., Galda, Alexey, Kumar, Sandeep, Kyoseva, Elica, Batista, Victor S.
The nexus of quantum computing and machine learning - quantum machine learning - offers the potential for significant advancements in chemistry. This review specifically explores the potential of quantum neural networks on gate-based quantum computer
Externí odkaz:
http://arxiv.org/abs/2409.15645
Toxicity is a roadblock that prevents an inordinate number of drugs from being used in potentially life-saving applications. Deep learning provides a promising solution to finding ideal drug candidates; however, the vastness of chemical space coupled
Externí odkaz:
http://arxiv.org/abs/2403.18997
As the rapidly evolving field of machine learning continues to produce incredibly useful tools and models, the potential for quantum computing to provide speed up for machine learning algorithms is becoming increasingly desirable. In particular, quan
Externí odkaz:
http://arxiv.org/abs/2305.18961
Autor:
Smaldone AM; Department of Chemistry, Yale University, New Haven 06511, Connecticut, United States., Batista VS; Department of Chemistry, Yale University, New Haven 06511, Connecticut, United States.
Publikováno v:
Journal of chemical theory and computation [J Chem Theory Comput] 2024 Jun 11; Vol. 20 (11), pp. 4901-4908. Date of Electronic Publication: 2024 May 25.
