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Broadly speaking, I am interested in high-stakes applications of probabilistic machine learning techniques. The consequences of failure for an ML algorithm that monitors the sensors of an aircraft engine are very different from one that recognizes faces in social media photos or recommends music. These critical applications often place a high premium on principled uncertainty estimates, applicability to limited datasets and interpretability: something probabilistic machine learning techniques like Gaussian processes can offer. Marrying these completely data-driven techniques with physical modeling for more robust predictions and sensible extrapolations is also something that intrigues me.
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论文共 24 篇作者统计合作学者相似作者
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Guoxuan Xia,Duolikun Danier,Ayan Das ,Stathi Fotiadis, Farhang Nabiei,Ushnish Sengupta,Alberto Bernacchia
CoRR (2023)
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Computer Methods in Applied Mechanics and Engineering (2023): 116042-116042
IEEE CONFERENCE ON GLOBAL COMMUNICATIONS, GLOBECOM (2023): 4779-4784
SSCIpp.1149-1155, (2022)
EarthArXiv (California Digital Library) (2021)
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