65 citations · 111 across the 6 of their papers we have counts for
7 papers
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…
Unitary-Coupled Restricted Boltzmann Machine Ansatz for Quantum Simulations
Chang-yu Hsieh, Qiming Sun, Shengyu Zhang +1
Neural-Network Quantum State (NQS) has attracted significant interests as a powerful wave-function ansatz to model quantum phenomena. In particular, a variant of NQS based on the r…
Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models
Guangyong Chen, Pengfei Chen, Chang-Yu Hsieh +9
We introduce a new molecular dataset, named Alchemy, for developing machine learning models useful in chemistry and material science. As of June 20th 2019, the dataset comprises of…
The Enhancement of Interfacial Exciton Dissociation by Energetic Disorder is a Nonequilibrium Effect
Liang Shi, Chee Kong Lee, Adam P. Willard
The dissociation of excited electron-hole pairs is a microscopic process that is fundamental to the performance of photovoltaic systems. For this process to be successful, the oppo…