Zobrazeno 1 - 10
of 115
pro vyhledávání: '"Wu Jindi"'
Publikováno v:
Open Life Sciences, Vol 19, Iss 1, Pp 101850-31 (2024)
The taste and tenderness of meat are the main determinants of carcass quality in many countries. This study aimed to discuss the mechanisms of intramuscular fat deposition in grazing and house-breeding cattle. We performed transcriptome analysis to c
Externí odkaz:
https://doaj.org/article/7138ebada1f24276b19483b41c4f7534
Noisy Intermediate-Scale Quantum (NISQ) devices, while accessible via cloud platforms, face challenges due to limited availability and suboptimal quality. These challenges raise the risk of cloud providers offering fraudulent services. This emphasize
Externí odkaz:
http://arxiv.org/abs/2408.11203
Quantum networks serve as the means to transmit information, encoded in quantum bits or qubits, between quantum processors that are physically separated. Given the instability of qubits, the design of such networks is challenging, necessitating a car
Externí odkaz:
http://arxiv.org/abs/2310.13628
Federated Learning (FL) is a distributed machine learning approach that enables model training in communication efficient and privacy-preserving manner. The standard optimization method in FL is Federated Averaging (FedAvg), which performs multiple l
Externí odkaz:
http://arxiv.org/abs/2309.11378
Quantum computing has shown considerable promise for compute-intensive tasks in recent years. For instance, classification tasks based on quantum neural networks (QNN) have garnered significant interest from researchers and have been evaluated in var
Externí odkaz:
http://arxiv.org/abs/2307.11875
Autor:
Wu, Jindi1 (AUTHOR), He, Xige1,2 (AUTHOR), Yun, Xueyan1 (AUTHOR), Qi, Mei1 (AUTHOR), Menghe, Buren3 (AUTHOR), Chen, Lu1 (AUTHOR), Han, Yunfei1 (AUTHOR), Huang, Yajuan1 (AUTHOR), Wang, Mingxu1 (AUTHOR), Sha, Rina1 (AUTHOR), Borjigin, Gerelt1 (AUTHOR) bor_gerelt07@imau.edu.cn
Publikováno v:
Food Science & Nutrition. Oct2024, Vol. 12 Issue 10, p7591-7606. 16p.
Many recent machine learning tasks resort to quantum computing to improve classification accuracy and training efficiency by taking advantage of quantum mechanics, known as quantum machine learning (QML). The variational quantum circuit (VQC) is freq
Externí odkaz:
http://arxiv.org/abs/2208.07719
Variational quantum algorithms (VQAs) have recently received significant attention from the research community due to their promising performance in Noisy Intermediate-Scale Quantum computers (NISQ). However, VQAs run on parameterized quantum circuit
Externí odkaz:
http://arxiv.org/abs/2205.02666
Publikováno v:
In Cytokine March 2024 175