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QML-Lisbon Uni
AQIS 2021
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Variational Quantum Circuits-NTU
AQIS 2021
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Variational Quantum Circuits
AQIS 2021
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Challenges and Opportunities of Quantum Machine Learning
AQIS 2021
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Challenges and Opportunities of Quantum Machine Learning
AQIS 2021
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Challenges and Opportunities of Quantum Machine Learning
AQIS 2021
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Challenges and Opportunities of Quantum Machine Learning
第九屆台灣工業與應用數學會年會-8月7日(六)
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The power of quantum neural networks
MLQ 2021
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Copy of Challenges and Opportunities of Quantum Machine Learning
CSIE, NTU. 16 July 2019
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Challenges and Opportunities of Quantum Machine Learning
CSIE, NTU. 16 July 2019
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Copy of General Resource Theory
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Dimension Free Tail Inequalities and Applications
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Machine Learning Meets Quantum Computation
01 Aug 2019
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Copy of One-shot distillation in a general resource theory
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General Resource Theory
Banff Conference. July 2019
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Machine Learning Meets Quantum Computation
CSIE, NTU. 16 July 2019
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Quantum AI
Promotion Slides
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Quantum Machine Learning
QI school at Kyoto University, 18-20 of March 2019
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Parameterized Quantum Circuits
The Second Hong Kong - Shenzhen Workshop on Quantum Information Science
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Quantum computer, quantum software and beyond.
Academia Sinica 90th anniversary, Frontiers of Sciences and Humanities Seminar Series, Taipei, Taiwan, November 23, 2018.
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Parameterized Quantum Circuits
arXiv:1809.06056+1810.11922
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Quantum Machine Learning
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Common Information In Quantum Information Science
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Quantum Machine Learning
Slides used in SOC Silicon-based Quantum Computing Forum. Taipei, Taiwan, September 19, 2018.
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General Resource Theory
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QSI Intro
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Learning Quantum Objects
1st International Workshop on Quantum Software and Quantum Machine Learning
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Error Exponent Analysis in Quantum Source and Channel Coding
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Round Complexity of Quantum State Transformation
arXiv:1610.01998
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Superadditivity in trade-off capacities of quantum channels
arXiv:0811.4227+arXiv:0901.3038+arXiv:1708.04314
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AQIS 2017: Moderate Deviations for Classical-Quantum Channels
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AQIS 2017: Quantum Sphere-Packing Bounds with Polynomial Prefactors
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Quantum Moderate and Large Deviation Analysis