基本信息
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个人简介
My research goal is to develop and responsibly deploy generative AI for music and creativity, thereby unlocking and augmenting human creative potential. To this end, my work involves (1) improving machine learning methods for controllable generative modeling for music, audio, and other sequential data, and (2) deploying real-world interactive systems that allow a broader audience—inclusive of non-musicians—to harness generative music AI through intuitive controls.
研究兴趣
论文共 44 篇作者统计合作学者相似作者
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CoRR (2025)
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Jongmin Jung, Dongmin Kim, Sihun Lee, Seola Cho, Hyungjoon Soh, Irmak Bukey,Chris Donahue,Dasaem Jeong
arxiv(2025)
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North American Chapter of the Association for Computational Linguisticspp.55-65, (2025)
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arxiv(2025)
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CHI 2025pp.1-28, (2025)
CoRR (2024)
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CoRR (2024)
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International Society for Music Information Retrieval Conferencepp.680-687, (2024)
Yusong Wu,Tim Cooijmans,Kyle Kastner,Adam Roberts,Ian Simon,Alexander Scarlatos,Chris Donahue, Cassie Tarakajian,Shayegan Omidshafiei,Aaron Courville,Pablo Samuel Castro,Natasha Jaques, Cheng Zhi Huang
ICML 2024 (2024)
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PROCEEDINGS OF THE 37TH ANNUAL ACM SYMPOSIUM ON USER INTERFACE SOFTWARE AND TECHNOLOGY, USIT 2024 (2024)
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作者统计
#Papers: 45
#Citation: 5032
H-Index: 19
G-Index: 30
Sociability: 5
Diversity: 1
Activity: 14
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