Application of Machine Learning to Numerical Algebraic Geometry

dc.contributor.authorBrake, Danielle
dc.contributor.authorEricson, Sarah
dc.contributor.authorHessler, Dan
dc.date.accessioned2020-05-05T19:33:26Z
dc.date.available2020-05-05T19:33:26Z
dc.date.issued2018-04
dc.descriptionColor poster with text, graphs, and images.en_US
dc.description.abstractThe solution of arbitrary polynomial systems is an area of active research, and has many applications in math, science and engineering. This program, Bertini 2, builds on the success of the first Bertini program, and seeks to eventually replace it entirely, as a powerful numerical engine.en_US
dc.description.sponsorshipUniversity of Wisconsin--Eau Claire Office of Research and Sponsored Programs.en_US
dc.identifier.urihttp://digital.library.wisc.edu/1793/80069
dc.language.isoen_USen_US
dc.relation.ispartofseriesUSGZE AS589;
dc.subjectPostersen_US
dc.subjectMathematicsen_US
dc.subjectGeometryen_US
dc.subjectPython (programming language)en_US
dc.subjectBertini 2en_US
dc.subjectTensorFlowen_US
dc.titleApplication of Machine Learning to Numerical Algebraic Geometryen_US
dc.typePresentationen_US

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