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Youzhi Luo
Youzhi Luo
Ph.D. student, Department of Computer Science & Engineering, Texas A&M University
Verified email at tamu.edu - Homepage
Title
Cited by
Cited by
Year
GraphDF: A discrete flow model for molecular graph generation
Y Luo, K Yan, S Ji
Proceedings of the 38th International Conference on Machine Learning 139 …, 2021
1472021
DIG: A turnkey library for diving into graph deep learning research
M Liu, Y Luo, L Wang, Y Xie, H Yuan, S Gui, H Yu, Z Xu, J Zhang, Y Liu, ...
Journal of Machine Learning Research 22 (240), 1-9, 2021
113*2021
Generating 3D molecules for target protein binding
M Liu, Y Luo, K Uchino, K Maruhashi, S Ji
Proceedings of the 39th International Conference on Machine Learning 162 …, 2022
872022
Advanced graph and sequence neural networks for molecular property prediction and drug discovery
Z Wang, M Liu, Y Luo, Z Xu, Y Xie, L Wang, L Cai, Q Qi, Z Yuan, T Yang, ...
Bioinformatics 38 (9), 2579-2586, 2022
852022
Stochastic optimization of areas under precision-recall curves with provable convergence
Q Qi, Y Luo, Z Xu, S Ji, T Yang
Advances in neural information processing systems 34, 1752-1765, 2021
642021
An autoregressive flow model for 3d molecular geometry generation from scratch
Y Luo, S Ji
International Conference on Learning Representations (ICLR), 2022
632022
Artificial intelligence for science in quantum, atomistic, and continuum systems
X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y Xie, M Liu, Y Lin, Z Xu, K Yan, ...
arXiv preprint arXiv:2307.08423, 2023
452023
Learning fair graph representations via automated data augmentations
H Ling, Z Jiang, Y Luo, S Ji, N Zou
The Eleventh International Conference on Learning Representations, 2022
302022
Molecule3d: A benchmark for predicting 3d geometries from molecular graphs
Z Xu, Y Luo, X Zhang, X Xu, Y Xie, M Liu, K Dickerson, C Deng, M Nakata, ...
arXiv preprint arXiv:2110.01717, 2021
182021
Automated data augmentations for graph classification
Y Luo, M McThrow, WY Au, T Komikado, K Uchino, K Maruhash, S Ji
The Eleventh International Conference on Learning Representations, 2023
162023
Efficient approximations of complete interatomic potentials for crystal property prediction
Y Lin, K Yan, Y Luo, Y Liu, X Qian, S Ji
International Conference on Machine Learning, 21260-21287, 2023
142023
Joint learning of label and environment causal independence for graph out-of-distribution generalization
S Gui, M Liu, X Li, Y Luo, S Ji
Advances in Neural Information Processing Systems 36, 2024
102024
Fast quantum property prediction via deeper 2d and 3d graph networks
M Liu, C Fu, X Zhang, L Wang, Y Xie, H Yuan, Y Luo, Z Xu, S Xu, S Ji
arXiv preprint arXiv:2106.08551, 2021
92021
MoleculeKit: Machine learning methods for molecular property prediction and drug discovery
Z Wang, M Liu, Y Luo, Z Xu, Y Xie, L Wang, L Cai, S Ji
arXiv preprint arXiv:2012.01981, 2020
62020
Qh9: A quantum hamiltonian prediction benchmark for qm9 molecules
H Yu, M Liu, Y Luo, A Strasser, X Qian, X Qian, S Ji
Advances in Neural Information Processing Systems 36, 2024
52024
Towards Symmetry-Aware Generation of Periodic Materials
Y Luo, C Liu, S Ji
Advances in Neural Information Processing Systems 36, 2024
42024
3D Molecular Geometry Analysis with 2D Graphs
Z Xu, Y Xie, Y Luo, X Zhang, X Xu, M Liu, K Dickerson, C Deng, M Nakata, ...
Proceedings of the 2024 SIAM International Conference on Data Mining (SDM …, 2024
22024
Graph structure and feature extrapolation for out-of-distribution generalization
X Li, S Gui, Y Luo, S Ji
arXiv preprint arXiv:2306.08076, 2023
22023
Frontiers of Graph Neural Networks with DIG
S Ji, M Liu, Y Liu, Y Luo, L Wang, Y Xie, Z Xu, H Yu
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
2022
A Neural Network View of Kernel Methods
S Ji, Y Luo, Z Wang, Y Xie
2020
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Articles 1–20