Trainable Discrete Feature Embeddings for Quantum Machine Learning-Reference-Cited by-同舟云学术

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Trainable Discrete Feature Embeddings for Quantum Machine Learning

Published:2021-10 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE International Conference on Quantum Computing and Engineering (QCE)
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Author:

Thumwanit Napat,Lortaraprasert Chayaphol,Yano Hiroshi,Raymond Rudy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9605247/9605263/09605351.pdf?arnumber=9605351

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Quantum metric learning with fuzzy-informed learning;Physica A: Statistical Mechanics and its Applications;2024-06

2. Subtleties in the trainability of quantum machine learning models;Quantum Machine Intelligence;2023-05-15

3. MAQML: a Meta-approach to Quantum Machine Learning with Accentuated Sample Variations for Unobtrusive Mental Health Monitoring;Quantum Machine Intelligence;2023-04-05

4. Implementation Of Grover's and Shor's Algorithms In Quantum Machine Learning;2023 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE);2023-01-27

5. Training Parameterized Quantum Circuits with Triplet Loss;Machine Learning and Knowledge Discovery in Databases;2023

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