Obserwuj
Meng Liu
Meng Liu
Research Scientist, NVIDIA
Zweryfikowany adres z nvidia.com - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Towards deeper graph neural networks
M Liu, H Gao, S Ji
Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020
6912020
Spherical message passing for 3d molecular graphs
Y Liu, L Wang, M Liu, Y Lin, X Zhang, B Oztekin, S Ji
International Conference on Learning Representations (ICLR), 2022
351*2022
Non-local graph neural networks
M Liu, Z Wang, S Ji
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
2042021
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
150*2021
Generating 3d molecules for target protein binding
M Liu, Y Luo, K Uchino, K Maruhashi, S Ji
International Conference on Machine Learning, 13912-13924, 2022
1452022
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
1342023
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
1272022
Graphebm: Molecular graph generation with energy-based models
M Liu, K Yan, B Oztekin, S Ji
arXiv preprint arXiv:2102.00546, 2021
1072021
Diffbp: Generative diffusion of 3d molecules for target protein binding
H Lin, Y Huang, O Zhang, S Ma, M Liu, X Li, L Wu, J Wang, T Hou, SZ Li
Chemical Science 16 (3), 1417-1431, 2025
782025
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, 3945-3978, 2023
452023
GraphFM: Improving large-scale GNN training via feature momentum
H Yu, L Wang, B Wang, M Liu, T Yang, S Ji
International conference on machine learning, 25684-25701, 2022
452022
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
412021
Graph mixup with soft alignments
H Ling, Z Jiang, M Liu, S Ji, N Zou
International Conference on Machine Learning, 21335-21349, 2023
352023
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, 40487-40503, 2023
212023
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
162021
On the markov property of neural algorithmic reasoning: Analyses and methods
M Bohde, M Liu, A Saxton, S Ji
arXiv preprint arXiv:2403.04929, 2024
72024
Graph and geometry generative modeling for drug discovery
M Xu, M Liu, W Jin, S Ji, J Leskovec, S Ermon
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
72023
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, ...
arXiv preprint arXiv:2305.13315, 2023
42023
Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models
M Liu, H Liu, S Ji
The Eleventh International Conference on Learning Representations, 2022
42022
Empowering GNNs via Edge-Aware Weisfeiler-Lehman Algorithm
M Liu, H Yu, S Ji
4*2022
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Prace 1–20