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[01] Gus Xia - Expressive Collaborative Music Performance via Machine Learning
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Content provided by The Thesis Review and Sean Welleck. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Thesis Review and Sean Welleck or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Gus Xia is an assistant professor at New York University Shanghai. His research explores machine learning for music, with a goal of building intelligent systems that understand and extend musical creativity and expression. His PhD thesis is titled Expressive Collaborative Music Performance via Machine Learning, which we discuss in depth along with his ongoing research at the NYU Shanghai Music X Lab. - Gus Xia's homepage: https://www.cs.cmu.edu/~gxia/ - Thesis: http://reports-archive.adm.cs.cmu.edu/anon/ml2016/CMU-ML-16-103.pdf Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html
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Manage episode 302418444 series 2982803
Content provided by The Thesis Review and Sean Welleck. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Thesis Review and Sean Welleck or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Gus Xia is an assistant professor at New York University Shanghai. His research explores machine learning for music, with a goal of building intelligent systems that understand and extend musical creativity and expression. His PhD thesis is titled Expressive Collaborative Music Performance via Machine Learning, which we discuss in depth along with his ongoing research at the NYU Shanghai Music X Lab. - Gus Xia's homepage: https://www.cs.cmu.edu/~gxia/ - Thesis: http://reports-archive.adm.cs.cmu.edu/anon/ml2016/CMU-ML-16-103.pdf Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html
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