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How AI is improving simulations with smarter sampling techniques

dc.contributor.authorGordon, Rachel
dc.date.accessioned2024-11-25T14:44:45Z
dc.date.available2024-11-25T14:44:45Z
dc.date.issued2024-10-02
dc.identifier.urihttps://hdl.handle.net/1721.1/157668
dc.description.abstractMIT CSAIL researchers created an AI-powered method for low-discrepancy sampling, which uniformly distributes data points to boost simulation accuracy.en_US
dc.description.sponsorshipThis material is based upon work supported by the United States Air Force under Air Force Contract No. FA8702-15-D-0001.en_US
dc.language.isoen_USen_US
dc.publisherMIT Newsen_US
dc.subjectMIT CSAILen_US
dc.subjectLLSCen_US
dc.subjectAIen_US
dc.titleHow AI is improving simulations with smarter sampling techniquesen_US
dc.typeArticleen_US
dc.identifier.citationhttps://news.mit.edu/2024/how-ai-improving-simulations-smarter-sampling-techniques-1002en_US


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    Information about the MIT Lincoln Laboratory Supercomputing Center

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