Quantum Machine Learning
256 papers for year 2021
Showing 217-228 of 256
Quantum-enhanced neural networks in the neural tangent kernel framework
Kouhei Nakaji, Hiroyuki Tezuka, Naoki Yamamoto
QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits
Hanrui Wang, Yongshan Ding, Jiaqi Gu, Zirui Li, Yujun Lin, David Z. Pan, Frederic T. Chong, Song Han
Qurzon: A Prototype for a Divide and Conquer Based Quantum Compiler
Turbasu Chatterjee, Arnav Das, Shah Ishmam Mohtashim, Amit Saha, Amlan Chakrabarti
Recent advances for quantum classifiers
Weikang Li, Dong-Ling Deng
Reinforcement Learning vs. Gradient-Based Optimisation for Robust Energy Landscape Control of Spin-1/2 Quantum Networks
I. Khalid, C. A. Weidner, E. A. Jonckheere, S. G. Schirmer, F. C. Langbein
Reservoir Computing Approach to Quantum State Measurement
Gerasimos Angelatos, Saeed A. Khan, Hakan E. Türeci
Resonant quantum principal component analysis.
Li Z, Chai Z, Guo Y, Ji W, Wang M, Shi F, Wang Y, Lloyd S, Du J.
Revisiting dequantization and quantum advantage in learning tasks
Jordan Cotler, Hsin-Yuan Huang, Jarrod R. McClean
Robust and fast post-processing of single-shot spin qubit detection events with a neural network.
Struck T, Lindner J, Hollmann A, Schauer F, Schmidbauer A, Bougeard D, Schreiber LR.
Sample Complexity of Learning Parametric Quantum Circuits
Haoyuan Cai, Qi Ye, Dong-Ling Deng
Scalable Variational Quantum Circuits for Autoencoder-based Drug Discovery
Junde Li, Swaroop Ghosh
Scaling silicon-based quantum computing using CMOS technology
M. F. Gonzalez-Zalba, S. de Franceschi, E. Charbon, T. Meunier, M. Vinet, A. S. Dzurak