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Hsin-Yuan Huang
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2020 – today
- 2024
- [c12]Hsin-Yuan Huang, John Preskill, Mehdi Soleimanifar:
Certifying Almost All Quantum States with Few Single-Qubit Measurements. FOCS 2024: 1202-1206 - [c11]Chi-Fang Chen
, Hsin-Yuan Huang
Local Minima in Quantum Systems. STOC 2024: 1323-1330 - [c10]Hsin-Yuan Huang
Learning Shallow Quantum Circuits. STOC 2024: 1343-1351 - [i38]Hsin-Yuan Huang, Yunchao Liu, Michael Broughton, Isaac Kim, Anurag Anshu, Zeph Landau, Jarrod R. McClean:
Learning shallow quantum circuits. CoRR abs/2401.10095 (2024) - [i37]Hsin-Yuan Huang, John Preskill, Mehdi Soleimanifar:
Certifying almost all quantum states with few single-qubit measurements. CoRR abs/2404.07281 (2024) - [i36]Thomas Schuster, Jonas Haferkamp, Hsin-Yuan Huang:
Random unitaries in extremely low depth. CoRR abs/2407.07754 (2024) - [i35]Armando Angrisani, Alexander Schmidhuber, Manuel S. Rudolph
Classically estimating observables of noiseless quantum circuits. CoRR abs/2409.01706 (2024) - [i34]Sitan Chen, Jaume de Dios Pont, Jun-Ting Hsieh, Hsin-Yuan Huang, Jane Lange, Jerry Li:
Predicting quantum channels over general product distributions. CoRR abs/2409.03684 (2024) - [i33]Fermi Ma, Hsin-Yuan Huang:
How to Construct Random Unitaries. CoRR abs/2410.10116 (2024) - [i32]Jerry Huang, Laura Lewis, Hsin-Yuan Huang, John Preskill:
Predicting adaptively chosen observables in quantum systems. CoRR abs/2410.15501 (2024) - [i31]Fermi Ma, Hsin-Yuan Huang:
How to Construct Random Unitaries. IACR Cryptol. ePrint Arch. 2024: 1652 (2024) - 2023
- [c9]Amira Abbas, Robbie King, Hsin-Yuan Huang, William J. Huggins, Ramis Movassagh, Dar Gilboa, Jarrod R. McClean:
On quantum backpropagation, information reuse, and cheating measurement collapse. NeurIPS 2023 - [i30]Laura Lewis, Hsin-Yuan Huang, Viet T. Tran, Sebastian Lehner, Richard Kueng, John Preskill:
Improved machine learning algorithm for predicting ground state properties. CoRR abs/2301.13169 (2023) - [i29]Marco Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, Patrick J. Coles:
Challenges and Opportunities in Quantum Machine Learning. CoRR abs/2303.09491 (2023) - [i28]Sofiène Jerbi, Joe Gibbs, Manuel S. Rudolph, Matthias C. Caro
The power and limitations of learning quantum dynamics incoherently. CoRR abs/2303.12834 (2023) - [i27]Amira Abbas, Robbie King, Hsin-Yuan Huang, William J. Huggins, Ramis Movassagh, Dar Gilboa, Jarrod R. McClean:
On quantum backpropagation, information reuse, and cheating measurement collapse. CoRR abs/2305.13362 (2023) - [i26]Senrui Chen, Changhun Oh, Sisi Zhou, Hsin-Yuan Huang, Liang Jiang:
Tight bounds on Pauli channel learning without entanglement. CoRR abs/2309.13461 (2023) - [i25]Chi-Fang Chen, Hsin-Yuan Huang, John Preskill, Leo Zhou:
Local minima in quantum systems. CoRR abs/2309.16596 (2023) - [i24]Haimeng Zhao, Laura Lewis, Ishaan Kannan, Yihui Quek, Hsin-Yuan Huang, Matthias C. Caro
Learning quantum states and unitaries of bounded gate complexity. CoRR abs/2310.19882 (2023) - 2022
- [j3]Marco Cerezo
Challenges and opportunities in quantum machine learning. Nat. Comput. Sci. 2(9): 567-576 (2022) - [i23]Matthias C. Caro
Out-of-distribution generalization for learning quantum dynamics. CoRR abs/2204.10268 (2022) - [i22]Joe Gibbs, Zoë Holmes, Matthias C. Caro
Dynamical simulation via quantum machine learning with provable generalization. CoRR abs/2204.10269 (2022) - [i21]Hsin-Yuan Huang, Steven T. Flammia, John Preskill:
Foundations for learning from noisy quantum experiments. CoRR abs/2204.13691 (2022) - [i20]Hsin-Yuan Huang, Yu Tong, Di Fang, Yuan Su:
Learning many-body Hamiltonians with Heisenberg-limited scaling. CoRR abs/2210.03030 (2022) - [i19]Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li:
The Complexity of NISQ. CoRR abs/2210.07234 (2022) - [i18]Hsin-Yuan Huang, Sitan Chen, John Preskill:
Learning to predict arbitrary quantum processes. CoRR abs/2210.14894 (2022) - [i17]Katherine Van Kirk, Jordan Cotler, Hsin-Yuan Huang, Mikhail D. Lukin:
Hardware-efficient learning of quantum many-body states. CoRR abs/2212.06084 (2022) - 2021
- [j2]Yuan Su
Nearly tight Trotterization of interacting electrons. Quantum 5: 495 (2021) - [c8]Sitan Chen, Jordan Cotler, Hsin-Yuan Huang
Exponential Separations Between Learning With and Without Quantum Memory. FOCS 2021: 574-585 - [i16]Hsin-Yuan Huang, Richard Kueng, John Preskill:
Information-theoretic bounds on quantum advantage in machine learning. CoRR abs/2101.02464 (2021) - [i15]Hsin-Yuan Huang, Richard Kueng, John Preskill:
Efficient estimation of Pauli observables by derandomization. CoRR abs/2103.07510 (2021) - [i14]Hsin-Yuan Huang, Richard Kueng, Giacomo Torlai, Victor V. Albert, John Preskill:
Provably efficient machine learning for quantum many-body problems. CoRR abs/2106.12627 (2021) - [i13]Matthias C. Caro
Generalization in quantum machine learning from few training data. CoRR abs/2111.05292 (2021) - [i12]Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li:
A Hierarchy for Replica Quantum Advantage. CoRR abs/2111.05874 (2021) - [i11]Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li:
Exponential separations between learning with and without quantum memory. CoRR abs/2111.05881 (2021) - [i10]Hsin-Yuan Huang, Michael Broughton, Jordan Cotler, Sitan Chen, Jerry Li, Masoud Mohseni, Hartmut Neven, Ryan Babbush, Richard Kueng, John Preskill, Jarrod R. McClean:
Quantum advantage in learning from experiments. CoRR abs/2112.00778 (2021) - [i9]Jordan Cotler, Hsin-Yuan Huang, Jarrod R. McClean:
Revisiting dequantization and quantum advantage in learning tasks. CoRR abs/2112.00811 (2021) - 2020
- [i8]Hsin-Yuan Huang, Richard Kueng, John Preskill:
Predicting Many Properties of a Quantum System from Very Few Measurements. CoRR abs/2002.08953 (2020) - [i7]Andreas Elben
Mixed-state entanglement from local randomized measurements. CoRR abs/2007.06305 (2020) - [i6]Hsin-Yuan Huang, Michael Broughton, Masoud Mohseni, Ryan Babbush, Sergio Boixo, Hartmut Neven, Jarrod R. McClean:
Power of data in quantum machine learning. CoRR abs/2011.01938 (2020) - [i5]Yuan Su, Hsin-Yuan Huang, Earl T. Campbell:
Nearly tight Trotterization of interacting electrons. CoRR abs/2012.09194 (2020)
2010 – 2019
- 2019
- [c7]Hsin-Yuan Huang, Eunsol Choi, Wen-tau Yih:
FlowQA: Grasping Flow in History for Conversational Machine Comprehension. ICLR (Poster) 2019 - [i4]Hsin-Yuan Huang, Richard Kueng:
Predicting Features of Quantum Systems using Classical Shadows. CoRR abs/1908.08909 (2019) - [i3]Hsin-Yuan Huang, Kishor Bharti, Patrick Rebentrost:
Near-term quantum algorithms for linear systems of equations. CoRR abs/1909.07344 (2019) - 2018
- [c6]Hsin-Yuan Huang, Chenguang Zhu, Yelong Shen, Weizhu Chen:
FusionNet: Fusing via Fully-aware Attention with Application to Machine Comprehension. ICLR (Poster) 2018 - [i2]Hsin-Yuan Huang, Eunsol Choi, Wen-tau Yih:
FlowQA: Grasping Flow in History for Conversational Machine Comprehension. CoRR abs/1810.06683 (2018) - 2017
- [c5]Hsiang-Fu Yu, Hsin-Yuan Huang, Inderjit S. Dhillon, Chih-Jen Lin:
A Unified Algorithm for One-Cass Structured Matrix Factorization with Side Information. AAAI 2017: 2845-2851 - [i1]Hsin-Yuan Huang, Chenguang Zhu, Yelong Shen, Weizhu Chen:
FusionNet: Fusing via Fully-Aware Attention with Application to Machine Comprehension. CoRR abs/1711.07341 (2017) - 2016
- [c4]Hsin-Yuan Huang, Shuo-Han Yeh, Che-Tsung Lin, Shang-Hong Lai
Video stabilization with distortion correction for wide-angle lens dashcam. APSIPA 2016: 1-6 - [c3]Ping-Cheng Kuo, Hsin-Yuan Huang, Shang-Hong Lai
Lighting estimation from a single image containing multiple planes. MMSys 2016: 23:1-23:9 - [c2]Hsin-Yuan Huang, Chih-Jen Lin:
Linear and Kernel Classification: When to Use Which? SDM 2016: 216-224 - 2012
- [c1]Hsin-Yuan Huang, Jin-Yi Lin, Chih-Cheng Hsieh, Wen-Hsu Chang, Hann-Huei Tsai, Chin-Fong Chiu:
A 9.2b 47fJ/conversion-step asynchronous SAR ADC with input range prediction DAC switching. ISCAS 2012: 2353-2356
1990 – 1999
- 1995
- [j1]Hsin-Yuan Huang, Thomas G. Robertazzi, Aurel A. Lazar:
A Comparison of Information Based Deflection Strategies. Comput. Networks ISDN Syst. 27(9): 1399-1407 (1995)
Coauthor Index
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