134 citations · 574 across the 19 of their papers we have counts for
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Graph Self-Supervised Learning for Optoelectronic Properties of Organic Semiconductors
Zaixi Zhang, Qi Liu, Shengyu Zhang +3
The search for new high-performance organic semiconducting molecules is challenging due to the vastness of the chemical space, machine learning methods, particularly deep learning…
ProtGNN: Towards Self-Explaining Graph Neural Networks
Zaixi Zhang, Qi Liu, Hao Wang +2
Despite the recent progress in Graph Neural Networks (GNNs), it remains challenging to explain the predictions made by GNNs. Existing explanation methods mainly focus on post-hoc e…
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction
Zaixi Zhang, Qi Liu, Hao Wang +2
Predicting molecular properties with data-driven methods has drawn much attention in recent years. Particularly, Graph Neural Networks (GNNs) have demonstrated remarkable success i…
Variational Quantum Simulation of Chemical Dynamics with Quantum Computers
Chee-Kong Lee, Chang-Yu Hsieh, Shengyu Zhang +1
Classical simulation of real-space quantum dynamics is challenging due to the exponential scaling of computational cost with system dimensions. Quantum computer offers the potentia…
Simulation of Condensed-Phase Spectroscopy with Near-term Digital Quantum Computer
Chee-Kong Lee, Chang-Yu Hsieh, Shengyu Zhang +1
Spectroscopy is an indispensable tool in understanding the structures and dynamics of molecular systems. However computational modelling of spectroscopy is challenging due to the e…
Variational Quantum-Neural Hybrid Eigensolver
Shi-Xin Zhang, Zhou-Quan Wan, Chee-Kong Lee +3
The variational quantum eigensolver (VQE) is one of the most representative quantum algorithms in the noisy intermediate-size quantum (NISQ) era, and is generally speculated to del…
Simulating Energy Transfer in Molecular Systems with Digital Quantum Computers
Chee-Kong Lee, Jonathan Wei Zhong Lau, Liang Shi +1
Quantum computers have the potential to simulate chemical systems beyond the capability of classical computers. Recent developments in hybrid quantum-classical approaches enable th…