基本信息
浏览量:19
职业迁徙
个人简介
My research focuses on data-efficient learning under uncertainty, including work on reinforcement learning, active learning and Bayesian deep learning. I am also interested in applying machine learning to problems in science and engineering.
My work revolves around two common themes:
Reasoning about uncertainty: I believe that obtaining accurate uncertainty estimates is crucial for efficient data acquisition and exploration. Therefore, I use the language of probability and Bayesian inference to express and reason about uncertainty.
Exploiting prior knowledge: Efficient learning requires to equip models with the right inductive biases. In particular, I am interested in exploiting prior knowledge about the symmetries of the underlying problem, such as translation- or rotation-equivariance.
My work revolves around two common themes:
Reasoning about uncertainty: I believe that obtaining accurate uncertainty estimates is crucial for efficient data acquisition and exploration. Therefore, I use the language of probability and Bayesian inference to express and reason about uncertainty.
Exploiting prior knowledge: Efficient learning requires to equip models with the right inductive biases. In particular, I am interested in exploiting prior knowledge about the symmetries of the underlying problem, such as translation- or rotation-equivariance.
研究兴趣
论文共 8 篇作者统计合作学者相似作者
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Claudio Zeni,Robert Pinsler,Daniel Zügner, Andrew Fowler, Matthew Horton,Xiang Fu, Sasha Shysheya,Jonathan Crabbé, Lixin Sun, Jake Smith, Bichlien Nguyen, Hannes Schulz,
CoRR (2023)
引用0浏览0EI引用
0
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ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019) (2019): 6356-6367
引用128浏览0EI引用
128
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2019 International Conference on Robotics and Automation (ICRA) (2019): 7242-7248
引用5浏览0EIWOS引用
5
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semanticscholar(2018)
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0
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作者统计
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合作机构
D-Core
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