基本信息
浏览量:27
职业迁徙
个人简介
I research on the intersection of artificial intelligence and physics in general, including but not limited to:
(1) AI for physics: extracting physical insights (e.g. conservation laws and symmetries) from data, improving prediction accuracy and sampling efficiency for data analysis in physics;
(2) Physics for AI: developing effective theories to understand the dynamics and generalization of neural networks, and building physics-inspired machine learning models.
(1) AI for physics: extracting physical insights (e.g. conservation laws and symmetries) from data, improving prediction accuracy and sampling efficiency for data analysis in physics;
(2) Physics for AI: developing effective theories to understand the dynamics and generalization of neural networks, and building physics-inspired machine learning models.
研究兴趣
论文共 38 篇作者统计合作学者相似作者
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arxiv(2024)
引用0浏览0引用
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CoRR (2024)
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CoRR (2024)
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Eric J. Michaud,Isaac Liao, Vedang Lad,Ziming Liu, Anish Mudide, Chloe Loughridge, Zifan Carl Guo, Tara Rezaei Kheirkhah, Mateja Vukelić,Max Tegmark
CoRR (2024)
引用0浏览0EI引用
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PHYSICAL REVIEW Eno. 2 (2024): L023301-L023301
Ziming Liu, Yixuan Wang, Sachin Vaidya,Fabian Ruehle,James Halverson,Marin Soljačić, Thomas Y. Hou,Max Tegmark
arxiv(2024)
引用13浏览0引用
13
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ENTROPYno. 1 (2024)
arxiv(2024)
引用0浏览0引用
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CoRR (2024)
引用0浏览0EI引用
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CoRR (2023)
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