| A conditional multinomial mixture model for superset label learning L Liu, T Dietterich Advances in neural information processing systems 25, 2012 | 304 | 2012 |
| Predicting physics in mesh-reduced space with temporal attention X Han, H Gao, T Pfaff, JX Wang, LP Liu arXiv preprint arXiv:2201.09113, 2022 | 149 | 2022 |
| Learnability of the superset label learning problem L Liu, T Dietterich International conference on machine learning, 1629-1637, 2014 | 136 | 2014 |
| Gan ensemble for anomaly detection X Han, X Chen, LP Liu Proceedings of the AAAI Conference on Artificial Intelligence 35 (5), 4090-4097, 2021 | 120 | 2021 |
| Kriging convolutional networks G Appleby, L Liu, LP Liu Proceedings of the AAAI conference on artificial intelligence 34 (04), 3187-3194, 2020 | 110 | 2020 |
| Efficient and degree-guided graph generation via discrete diffusion modeling X Chen, J He, X Han, LP Liu arXiv preprint arXiv:2305.04111, 2023 | 107 | 2023 |
| Incorporating boosted regression trees into ecological latent variable models R Hutchinson, LP Liu, T Dietterich Proceedings of the AAAI Conference on Artificial Intelligence 25 (1), 1343-1348, 2011 | 89 | 2011 |
| Least square incremental linear discriminant analysis LP Liu, Y Jiang, ZH Zhou 2009 Ninth IEEE International Conference on Data Mining, 298-306, 2009 | 55 | 2009 |
| Bayesian conditional diffusion models for versatile spatiotemporal turbulence generation H Gao, X Han, X Fan, L Sun, LP Liu, L Duan, JX Wang Computer Methods in Applied Mechanics and Engineering 427, 117023, 2024 | 50 | 2024 |
| Order matters: Probabilistic modeling of node sequence for graph generation X Chen, X Han, J Hu, FJR Ruiz, L Liu arXiv preprint arXiv:2106.06189, 2021 | 41 | 2021 |
| MassSpecGym: A benchmark for the discovery and identification of molecules R Bushuiev, A Bushuiev, NF de Jonge, A Young, F Kretschmer, ... Advances in Neural Information Processing Systems 37, 110010-110027, 2024 | 38 | 2024 |
| Nvdiff: Graph generation through the diffusion of node vectors X Chen, Y Li, A Zhang, L Liu arXiv preprint arXiv:2211.10794, 2022 | 32 | 2022 |
| TEFE: A time-efficient approach to feature extraction LP Liu, Y Yu, Y Jiang, ZH Zhou 2008 Eighth IEEE International Conference on Data Mining, 423-432, 2008 | 29 | 2008 |
| Using graph neural networks for site-of-metabolism prediction and its applications to ranking promiscuous enzymatic products V Porokhin, LP Liu, S Hassoun Bioinformatics 39 (3), btad089, 2023 | 28 | 2023 |
| Stochastic iterative graph matching L Liu, MC Hughes, S Hassoun, L Liu International Conference on Machine Learning, 6815-6825, 2021 | 25 | 2021 |
| Learning graph representations of biochemical networks and its application to enzymatic link prediction J Jiang, LP Liu, S Hassoun Bioinformatics 37 (6), 793-799, 2021 | 25 | 2021 |
| Reason out your layout: Evoking the layout master from large language models for text-to-image synthesis X Chen, Y Liu, Y Yang, J Yuan, Q You, LP Liu, H Yang arXiv preprint arXiv:2311.17126, 2023 | 24 | 2023 |
| Using graph neural networks for mass spectrometry prediction H Zhu, L Liu, S Hassoun arXiv preprint arXiv:2010.04661, 2020 | 24 | 2020 |
| An Ensemble Spectral Prediction (ESP) model for metabolite annotation X Li, Y Zhou Chen, A Kalia, H Zhu, L Liu, S Hassoun Bioinformatics 40 (8), btae490, 2024 | 23 | 2024 |
| Transductive optimization of top k precision LP Liu, TG Dietterich, N Li, ZH Zhou arXiv preprint arXiv:1510.05976, 2015 | 21 | 2015 |
Xiaohui ChenMetaVerified email at tufts.edu
