基本信息
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职业迁徙
个人简介
I study meaningful pretext tasks, prescribed from human knowledge, for computer vision, natural language processing and science problems. I have worked on fundamental machine learning systems that generalize well across
a variety of domains. In particular, I have tackled real world problems, such as text summarization of scientific
articles, by developing methods inspired by fundamental science, such as novel recurrent neural networks that use
rotations to remember and recall information better or efficient convolutional layers based on optimal connectivity
patterns.
Keywords: physics-inspired, self-supervised learning, transfer learning, meta learning, AI accelerators.
研究兴趣
论文共 41 篇作者统计合作学者相似作者
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Seou Choi,Yannick Salamin,Charles Roques-Carmes,Rumen Dangovski,Di Luo,Zhuo Chen, Michael Horodynski,Jamison Sloan, Shiekh Zia Uddin,Marin Soljacic
arxiv(2024)
2023 IEEE HIGH PERFORMANCE EXTREME COMPUTING CONFERENCE, HPECpp.1-9, (2023)
2023 IEEE HIGH PERFORMANCE EXTREME COMPUTING CONFERENCE, HPECpp.1-8, (2023)
2023 IEEE HIGH PERFORMANCE EXTREME COMPUTING CONFERENCE, HPECpp.1-12, (2023)
arxiv(2023)
Viggo Moro,Charlotte Loh,Rumen Dangovski,Ali Ghorashi, Andrew Ma,Zhuo Chen, Samuel Kim,Peter Y. Lu,Thomas Christensen,Marin Soljačić
arxiv(2023)
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2023 IEEE HIGH PERFORMANCE EXTREME COMPUTING CONFERENCE, HPECpp.1-13, (2023)
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