5 citations · 7 across the 6 of their papers we have counts for
7 papers
Turning Quantum Compiler Configuration Selection Upside Down: A Top-Down Paradigm
Ming Zhong, Xiangyu Ren, Kangyu Zheng +4
Selecting an effective quantum compiler configuration requires coordinated decisions over both hardware targets and compiler settings, with the ultimate goal of improving circuit e…
SQD-Enabled Circuit Compression for Resource-Efficient Quantum Chemistry
Kangyu Zheng, Yidong Zhou, Jinglei Cheng +3
Sample-based Quantum Diagonalization (SQD) recovers ground-state energies by classically diagonalizing a Hamiltonian in the subspace spanned by quantum samples, requiring only bits…
Q-Score: A Quantum-Native Scoring Function for Molecular Docking
Kangyu Zheng, Yidong Zhou, Ruihao Li +3
Molecular docking predicts how a small molecule binds to a protein and is a key bottleneck in drug discovery. Classical scoring functions sum empirical pairwise contacts, blind to…
Beyond Affinity: A Benchmark of 1D, 2D, and 3D Methods Reveals Critical Trade-offs in Structure-Based Drug Design
Kangyu Zheng, Kai Zhang, Jiale Tan +7
Currently, the field of structure-based drug design is dominated by three main types of algorithms: search-based algorithms, deep generative models, and reinforcement learning. Whi…
QCS-ADME: Quantum Circuit Search for Drug Property Prediction with Imbalanced Data and Regression Adaptation
Kangyu Zheng, Tianfan Fu, Zhiding Liang
The biomedical field is beginning to explore the use of quantum machine learning (QML) for tasks traditionally handled by classical machine learning, especially in predicting ADME…
Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate?
Kangyu Zheng, Yingzhou Lu, Zaixi Zhang +4
Currently, the field of structure-based drug design is dominated by three main types of algorithms: search-based algorithms, deep generative models, and reinforcement learning. Whi…
Argus: Benchmarking and Enhancing Vision-Language Models for 3D Radiology Report Generation
Che Liu, Zhongwei Wan, Yuqi Wang +5
Automatic radiology report generation holds significant potential to streamline the labor-intensive process of report writing by radiologists, particularly for 3D radiographs such…