Xianggen Liu
Cited by
Cited by
Contrastive learning of subject-invariant EEG representations for cross-subject emotion recognition
X Shen, X Liu, X Hu, D Zhang, S Song
IEEE Transactions on Affective Computing 14 (3), 2496-2511, 2022
Unsupervised Paraphrasing by Simulated Annealing
X Liu, L Mou, F Meng, H Zhou, J Zhou, S Song
ACL, 302–312, 2020
Deep geometric representations for modeling effects of mutations on protein-protein binding affinity
X Liu, Y Luo, P Li, S Song, J Peng
PLoS computational biology 17 (8), e1009284, 2021
TrimNet: learning molecular representation from triplet messages for biomedicine
P Li, Y Li, CY Hsieh, S Zhang, X Liu, H Liu, S Song, X Yao
Briefings in Bioinformatics 22 (4), bbaa266, 2021
Addressnet: Shift-based primitives for efficient convolutional neural networks
Y He, X Liu, H Zhong, Y Ma
2019 IEEE Winter conference on applications of computer vision (WACV), 1213-1222, 2019
Finding decision jumps in text classification
X Liu, L Mou, H Cui, Z Lu, S Song
Neurocomputing 371, 177-187, 2020
Jumper: Learning when to make classification decisions in reading
X Liu, L Mou, H Cui, Z Lu, S Song
IJCAI, 4237-4243, 2018
Pairwise Half-graph Discrimination: A Simple Graph-level Self-supervised Strategy for Pre-training Graph Neural Networks
P Li, J Wang, Z Li, Y Qiao, X Liu, F Ma, P Gao, S Song, G Xie
IJCAI, 2694-2700, 2021
Simulated annealing for optimization of graphs and sequences
X Liu, P Li, F Meng, H Zhou, H Zhong, J Zhou, L Mou, S Song
Neurocomputing 465, 310-324, 2021
A chance-constrained generative framework for sequence optimization
X Liu, Q Liu, S Song, J Peng
International Conference on Machine Learning, 6271-6281, 2020
Msgnet: Learning multi-scale inter-series correlations for multivariate time series forecasting
W Cai, Y Liang, X Liu, J Feng, Y Wu
Proceedings of the AAAI Conference on Artificial Intelligence 38 (10), 11141 …, 2024
Object-oriented neural programming (oonp) for document understanding
Z Lu, X Liu, H Cui, Y Yan, D Zheng
ACL, 2717–2726, 2018
Gpt-nas: Neural architecture search with the generative pre-trained model
C Yu, X Liu, C Tang, W Feng, J Lv
arXiv preprint arXiv:2305.05351, 2023
Abstract Rule Learning for Paraphrase Generation.
X Liu, W Lei, J Lv, J Zhou, LD Raedt
IJCAI, 4273-4279, 2022
Riboexp: an interpretable reinforcement learning framework for ribosome density modeling
H Hu, X Liu, A Xiao, YY Li, C Zhang, T Jiang, D Zhao, S Song, J Zeng
Briefings in Bioinformatics 22 (5), bbaa412, 2021
Learning robust rule representations for abstract reasoning via internal inferences
W Zhang, S Mo, X Liu, S Song
Advances in Neural Information Processing Systems 35, 33550-33562, 2022
Decomposing Retrosynthesis into Reactive Center Prediction and Molecule Generation
X Liu, P Li, S Song
bioRxiv, 677849, 2019
Searching safe landing site with parameters optimization based on genetic algorithm
X Liu, H Zhong, S Chang, Y Meng
2014 11th International Computer Conference on Wavelet Actiev Media …, 2014
Powerformer: A temporal-based transformer model for wind power forecasting
S Mo, H Wang, B Li, Z Xue, S Fan, X Liu
Energy Reports 11, 736-744, 2024
Iml-vit: Image manipulation localization by vision transformer
X Ma, B Du, X Liu, AYA Hammadi, J Zhou
arXiv preprint arXiv:2307.14863, 2023
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