92 citations · 186 across the 7 of their papers we have counts for
7 papers
When AI meets quantum information: A comprehensive review
Min Chen, Yu Gan, Xin Jin +15
Artificial intelligence (AI) and quantum information (QI) are rapidly co-evolving. AI is becoming a practical tool for learning, designing, controlling, and verifying quantum syste…
Learning with errors may remain hard against quantum holographic attacks
Yunfei Wang, Xin Jin, Junyu Liu
The Learning with Errors (LWE) problem underlies modern lattice-based cryptography and is assumed to be quantum hard. Recent results show that estimating entanglement entropy is as…
Towards efficient quantum algorithms for diffusion probabilistic models
Yunfei Wang, Ruoxi Jiang, Yingda Fan +4
A diffusion probabilistic model (DPM) is a generative model renowned for its ability to produce high-quality outputs in tasks such as image and audio generation. However, training…
A comprehensive review of Quantum Machine Learning: from NISQ to Fault Tolerance
Yunfei Wang, Junyu Liu
Quantum machine learning, which involves running machine learning algorithms on quantum devices, has garnered significant attention in both academic and business circles. In this p…
SU(d)-Symmetric Random Unitaries: Quantum Scrambling, Error Correction, and Machine Learning
Zimu Li, Han Zheng, Yunfei Wang +3
Quantum information processing in the presence of continuous symmetry is of wide importance and exhibits many novel physical and mathematical phenomena. SU(d) is a continuous group…
Fundamental causal bounds of quantum random access memories
Yunfei Wang, Yuri Alexeev, Liang Jiang +2
Quantum devices should operate in adherence to quantum physics principles. Quantum random access memory (QRAM), a fundamental component of many essential quantum algorithms for tas…
Towards provably efficient quantum algorithms for large-scale machine-learning models
Junyu Liu, Minzhao Liu, Jin-Peng Liu +5
Large machine learning models are revolutionary technologies of artificial intelligence whose bottlenecks include huge computational expenses, power, and time used both in the pre-…