| Motif-based graph self-supervised learning for molecular property prediction Z Zhang, Q Liu, H Wang, C Lu, CK Lee Advances in Neural Information Processing Systems 34, 15870-15882, 2021 | 277 | 2021 |
| Nanoscale transport of charge-transfer states in organic donor–acceptor blends PB Deotare, W Chang, E Hontz, DN Congreve, L Shi, PD Reusswig, ... Nature materials 14 (11), 1130-1134, 2015 | 199 | 2015 |
| ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction Z Hao, C Lu, Z Hu, H Wang, Z Huang, Q Liu, E Chen, CK Lee The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020 | 156 | 2020 |
| ProtGNN: Towards self-explaining graph neural networks Z Zhang, Q Liu, H Wang, C Lu, CK Lee Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 9127-9135, 2022 | 138 | 2022 |
| Accuracy of second order perturbation theory in the polaron and variational polaron frames CK Lee, J Moix, J Cao The Journal of chemical physics 136 (20), 2012 | 130 | 2012 |
| Tensorcircuit: a quantum software framework for the nisq era SX Zhang, J Allcock, ZQ Wan, S Liu, J Sun, H Yu, XH Yang, J Qiu, Z Ye, ... Quantum 7, 912, 2023 | 89 | 2023 |
| Alchemy: A quantum chemistry dataset for benchmarking AI models G Chen, P Chen, CY Hsieh, CK Lee, B Liao, R Liao, W Liu, J Qiu, Q Sun, ... arXiv:1906.09427 ICLR workshop 2019, 2019 | 86 | 2019 |
| Hierarchical graph transformer with adaptive node sampling Z Zhang, Q Liu, Q Hu, CK Lee Advances in Neural Information Processing Systems 35, 21171-21183, 2022 | 79 | 2022 |
| Excitonic energy transfer in light-harvesting complexes in purple bacteria J Ye, K Sun, Y Zhao, Y Yu, CK Lee, J Cao The Journal of Chemical Physics 136 (24), 06B619, 2012 | 73 | 2012 |
| Coherent quantum transport in disordered systems: A unified polaron treatment of hopping and band-like transport CK Lee, J Moix, J Cao The Journal of chemical physics 142 (16), 2015 | 69 | 2015 |
| Noncanonical statistics of a spin-boson model: Theory and exact Monte Carlo simulations CK Lee, J Cao, J Gong Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 86 (2 …, 2012 | 65 | 2012 |
| The Enhancement of Interfacial Exciton Dissociation by Energetic Disorder Is a Nonequilibrium Effect L Shi*, CK Lee*, AP Willard ACS central science, 2017 | 61 | 2017 |
| Quantum diffusion on molecular tubes: Universal scaling of the 1D to 2D transition C Chuang, CK Lee, JM Moix, J Knoester, J Cao Physical review letters 116 (19), 196803, 2016 | 52 | 2016 |
| Variational quantum-neural hybrid eigensolver SX Zhang, ZQ Wan, CK Lee, CY Hsieh, S Zhang, H Yao Physical Review Letters 128 (12), 120502, 2022 | 45 | 2022 |
| Deep learning for optoelectronic properties of organic semiconductors C Lu, Q Liu, Q Sun, CY Hsieh, S Zhang, L Shi, CK Lee The Journal of Physical Chemistry C 124 (13), 7048-7060, 2020 | 45 | 2020 |
| Optimizing quantum annealing schedules with Monte Carlo tree search enhanced with neural networks YQ Chen, Y Chen, CK Lee, S Zhang, CY Hsieh Nature Machine Intelligence 4 (3), 269-278, 2022 | 39* | 2022 |
| Transfer learning with graph neural networks for optoelectronic properties of conjugated oligomers CK Lee, C Lu, Y Yu, Q Sun, CY Hsieh, S Zhang, Q Liu, L Shi The Journal of Chemical Physics 154 (2), 2021 | 37 | 2021 |
| Neural-network variational quantum algorithm for simulating many-body dynamics CK Lee, P Patil, S Zhang, CY Hsieh Physical Review Research 3 (2), 023095, 2021 | 34 | 2021 |
| Model inversion attacks against graph neural networks Z Zhang, Q Liu, Z Huang, H Wang, CK Lee, E Chen IEEE Transactions on Knowledge and Data Engineering 35 (9), 8729-8741, 2022 | 33 | 2022 |
| Machine learning Frenkel Hamiltonian parameters to accelerate simulations of exciton dynamics A Farahvash, CK Lee, Q Sun, L Shi, AP Willard The Journal of Chemical Physics 153 (7), 2020 | 33 | 2020 |
Liang ShiUniversity of California, MercedVerified email at ucmerced.edu
