Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Minzhao Liu"'
Autor:
Junyu Liu, Minzhao Liu, Jin-Peng Liu, Ziyu Ye, Yunfei Wang, Yuri Alexeev, Jens Eisert, Liang Jiang
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-6 (2024)
Abstract Large machine learning models are revolutionary technologies of artificial intelligence whose bottlenecks include huge computational expenses, power, and time used both in the pre-training and fine-tuning process. In this work, we show that
Externí odkaz:
https://doaj.org/article/280da3c96c15499cb7a5adc603d1bc07
Publikováno v:
npj Quantum Information, Vol 8, Iss 1, Pp 1-8 (2022)
Abstract Random quantum circuits have been utilized in the contexts of quantum supremacy demonstrations, variational quantum algorithms for chemistry and machine learning, and blackhole information. The ability of random circuits to approximate any r
Externí odkaz:
https://doaj.org/article/e8df57b52c44432db385c11491d47db0
Large machine learning models are revolutionary technologies of artificial intelligence whose bottlenecks include huge computational expenses, power, and time used both in the pre-training and fine-tuning process. In this work, we show that fault-tol
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8e286733cffdd08c2eaa146a757f6254
https://doi.org/10.21203/rs.3.rs-2860733/v1
https://doi.org/10.21203/rs.3.rs-2860733/v1
Publikováno v:
2022 IEEE/ACM Third International Workshop on Quantum Computing Software (QCS).
Noisy quantum simulation is challenging since one has to take into account the stochastic nature of the process. The dominating method for it is the density matrix approach. In this paper, we evaluate conditions for which this method is inferior to a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b7d564b90fd2bd3db73a50dabcf7058
https://doi.org/10.1109/qcs56647.2022.00018
https://doi.org/10.1109/qcs56647.2022.00018
Publikováno v:
2022 IEEE International Conference on Quantum Computing and Engineering (QCE).
Quantum embedding learning is an important step in the application of quantum machine learning to classical data. In this paper we propose a quantum few-shot embedding learning paradigm, which learns embeddings useful for training downstream quantum
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fda915ad8e39ab0e06b0961652d29abb
https://doi.org/10.1109/qce53715.2022.00026
https://doi.org/10.1109/qce53715.2022.00026
Publikováno v:
Emerging Topics in Artificial Intelligence 2020.
Recently, deep neural network (DNN) based adaptive optics systems were proposed to address the issue of latency in existing wavefront sensorless (WFS-less) aberration correction techniques. Intensity images alone are sufficient for the DNN model to c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ce8b0f0ad7ec6b8de2fdca322f1c7c5
https://doi.org/10.1117/12.2569647
https://doi.org/10.1117/12.2569647
Autor:
Ronald I. Shorr, Teresa M. Waters, Lorraine C. Mion, Minzhao Liu, Nancy Dunton, Vincent S. Staggs, Michael J. Daniels
Publikováno v:
Journal of hospital medicine. 14
Background The Centers for Medicare & Medicaid Services (CMS) implemented the Hospital-Acquired Conditions (HACs) Initiative in October 2008; the CMS no longer reimbursed hospitals for fall injury. The effects of this payment change on fall and fall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a53bd982c3b4e57a0862a6626d54bd1c
https://pubmed.ncbi.nlm.nih.gov/31532748
https://pubmed.ncbi.nlm.nih.gov/31532748
Publikováno v:
Biostatistics. 17:108-121
In this paper, we develop methods for longitudinal quantile regression when there is monotone missingness. In particular, we propose pattern mixture models with a constraint that provides a straightforward interpretation of the marginal quantile regr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9aebb76a7830b73687452e8ed686b441
https://doi.org/10.1093/biostatistics/kxv023
https://doi.org/10.1093/biostatistics/kxv023
Autor:
Minzhao Liu, Michael J. Daniels, Nancy Dunton, Elena M. Andresen, Erin D. Bouldin, Lorraine C. Mion, Michael Simon, Ronald I. Shorr, Teresa M. Waters
Objectives: The purpose of this study was to provide normative data on fall prevalence in U.S. hospitals by unit type and to determine the 27-month secular trend in falls before the implementation of the Centers for Medicare and Medicaid Service (CMS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d3adbb2f83f7f38cfdc7f6d86ea9af1a
https://europepmc.org/articles/PMC3572247/
https://europepmc.org/articles/PMC3572247/