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个人简介
Risi Kondor’s work is centered on basic machine learning methodology, often inspired by ideas from algebra and computational harmonic analysis. In recent years, much of the work in Risi’s lab has focused on the rapidly growing intersection between machine learning and science, including novel graph neural network architectures for chemistry, machine learning approaches to learning molecular force fields, and neural network approximations to quantum states. As part of this endeavor, his group has made foundational contributions to the theory of group equivariant neural networks, which are used in physics and chemistry, as well as computer vision and medical imaging. An integral part of the group’s work is the development of high performance, open source software libraries.
研究兴趣
论文共 88 篇作者统计合作学者相似作者
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MACHINE LEARNING-SCIENCE AND TECHNOLOGYno. 2 (2024): 025044
International Conference on Artificial Intelligence and Statisticspp.424-432, (2024)
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CoRR (2024)
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arXiv (Cornell University) (2023)
CoRR (2023)
JOURNAL OF CHEMICAL PHYSICSno. 3 (2023)
CoRR (2023)
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作者统计
#Papers: 87
#Citation: 7394
H-Index: 27
G-Index: 67
Sociability: 5
Diversity: 2
Activity: 33
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