14 citations · 17 across the 7 of their papers we have counts for
9 papers
QuSema: Detecting Silent Bugs in Quantum Libraries via Quantum-knowledge-enhanced Agents
Yujin Song, Kaining Zhang, Qixin Zhang +3
Quantum libraries are now critical infrastructure for quantum algorithm development, yet their correctness remains difficult to test. Existing testing techniques mainly rely on fai…
Stochastic Pauli-path simulator for large-scale quantum optimization
Kaining Zhang, Xinbiao Wang, Kunsheng Li +4
Pauli-based simulators offer a promising route to large-scale classical simulation of quantum circuits in the low-magic regime. Yet their applicability remains largely limited to f…
AQER: a scalable and efficient data loader for digital quantum computers
Kaining Zhang, Xinbiao Wang, Yuxuan Du +2
Digital quantum computing promises to offer computational capabilities beyond the reach of classical systems, yet its capabilities are often challenged by scarce quantum resources.…
Mitigating Barren Plateaus in Quantum Denoising Diffusion Probabilistic Model
Haipeng Cao, Kaining Zhang, Dacheng Tao +1
Quantum generative models exploit quantum superposition and entanglement to enhance learning efficiency for both classical and quantum data. Recently, inspired by classical diffusi…
AiDE-Q: Synthetic Labeled Datasets Can Enhance Learning Models for Quantum Property Estimation
Xinbiao Wang, Yuxuan Du, Zihan Lou +5
Quantum many-body problems are central to various scientific disciplines, yet their ground-state properties are intrinsically challenging to estimate. Recent advances in deep learn…
TITAN: A Trajectory-Informed Technique for Adaptive Parameter Freezing in Large-Scale VQE
Yifeng Peng, Xinyi Li, Samuel Yen-Chi Chen +4
Variational quantum Eigensolver (VQE) is a leading candidate for harnessing quantum computers to advance quantum chemistry and materials simulations, yet its training efficiency de…
Quantum Machine Learning: A Hands-on Tutorial for Machine Learning Practitioners and Researchers
Yuxuan Du, Xinbiao Wang, Naixu Guo +6
This tutorial intends to introduce readers with a background in AI to quantum machine learning (QML) -- a rapidly evolving field that seeks to leverage the power of quantum compute…
The curse of random quantum data
Kaining Zhang, Junyu Liu, Liu Liu +3
Quantum machine learning, which involves running machine learning algorithms on quantum devices, may be one of the most significant flagship applications for these devices. Unlike…
A Comprehensive Review on Deep Supervision: Theories and Applications
Renjie Li, Xinyi Wang, Guan Huang +7
Deep supervision, or known as 'intermediate supervision' or 'auxiliary supervision', is to add supervision at hidden layers of a neural network. This technique has been increasingl…