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Yuan Mei
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Yuan Mei12 visible / 12 total nodes / 22 links

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Related contextCo-authorshipCo-authorshipCo-authorshipWorks onWorks onWorks onWorks onAuthorshipWorks onWorks onAuthorshipAuthorshipAuthorshipAuthorshipTopic signalTopic signalTopic signalAuthorshipAuthorshipAuthorshipAuthorshipYuan MeiAYuan MeiResearcherDeterministic Decomposition of Stochastic Generative DynamicsWDeterministic Decomposi...preprint / 2026Xingyu SongAXingyu SongResearcherNaoya TakeishiANaoya TakeishiResearcherA direct-sampling RF receiver for MOLLER beam charge measurementWA direct-sampling RF re...preprint / 2021Machine LearningTMachine Learning49008 worksArtificial IntelligenceTArtificial Intelligence22915 worksPFL-MoE: Personalized Federated Learning Based on Mixture of ExpertsWPFL-MoE: Personalized F...preprint / 2020Cryogenic Characterization of 180 nm CMOS Technology at 100 mKWCryogenic Characterizat...preprint / 2020Development of a highly pixelated direct charge sensor, Topmetal-I, for ionizing radiation imagingWDevelopment of a highly...preprint / 2014Monolithic Active Pixel Sensors on CMOS technologiesWMonolithic Active Pixel...preprint / 2022Topmetal-M: a novel pixel sensor for compact tracking applicationsWTopmetal-M: a novel pix...preprint / 2022
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Yuan Mei

Researcher

PaperDeterministic Decomposition of Stochastic Generative DynamicsAuthorship / preprint / 2026PersonXingyu SongCo-authorship / ResearcherPersonNaoya TakeishiCo-authorship / ResearcherPaperA direct-sampling RF receiver for MOLLER beam charge measurementAuthorship / preprint / 2021TopicMachine LearningWorks on / 49008 worksTopicArtificial IntelligenceWorks on / 22915 worksPaperPFL-MoE: Personalized Federated Learning Based on Mixture of ExpertsAuthorship / preprint / 2020PaperCryogenic Characterization of 180 nm CMOS Technology at 100 mKAuthorship / preprint / 2020

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