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Bin Shan
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Journal Articles
- 2023
- [j5]Bo Yang
, Feng Liu, Liang Xue
, Bin Shan:
Fault-Tolerant SINS/Doppler Radar/Odometer Integrated Navigation Method Based on Two-Stage Fault Detection Structure. Entropy 25(10): 1412 (2023) - [j4]Wen Guo
, Dong Li, Bowen Liang, Bin Shan:
Multi-view region proposal network predictive learning for tracking. Multim. Syst. 29(1): 333-346 (2023) - 2022
- [j3]Wen Guo
, Yuelong Jin, Bin Shan, Xinmiao Ding, Minghao Wang:
Multi-cue multi-hypothesis tracking with re-identification for multi-object tracking. Multim. Syst. 28(3): 925-937 (2022) - 2015
- [j2]Lin Deng, Yun Zhang
, Yanwei Wen
, Bin Shan, Huamin Zhou:
A fractional-step thermal lattice Boltzmann model for high Peclet number flow. Comput. Math. Appl. 70(5): 1152-1161 (2015) - [j1]Wenjie He, Hai-Tao Zhang, Zhiyong Chen, Bo Chu, Kun Cao
, Bin Shan, Rong Chen:
Generalized Predictive Control of Temperature on an Atomic Layer Deposition Reactor. IEEE Trans. Control. Syst. Technol. 23(6): 2408-2415 (2015)
Conference and Workshop Papers
- 2022
- [c3]Ye Li, Yiwen Pang, Bin Shan:
Physics-guided Data Augmentation for Learning the Solution Operator of Linear Differential Equations. CCIS 2022: 543-547 - 2017
- [c2]Bin Shan, Hao Wang, Yves Lepage:
Unsupervised Bilingual Segmentation using MDL for Machine Translation. PACLIC 2017: 89-96 - 2014
- [c1]Chen Ping, Zhengyan Zhang, Dingfang Chen, Jiquan Hu, Bin Shan, Li Bo:
Topological Reconstruction Based on STL Model. HCC 2014: 693-700
Informal and Other Publications
- 2023
- [i5]Siqi Chen, Bin Shan, Ye Li:
Efficient Discrete Physics-informed Neural Networks for Addressing Evolutionary Partial Differential Equations. CoRR abs/2312.14608 (2023) - 2022
- [i4]Bin Shan, Weichong Yin, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang:
ERNIE-ViL 2.0: Multi-view Contrastive Learning for Image-Text Pre-training. CoRR abs/2209.15270 (2022) - [i3]Bin Shan, Yaqian Han, Weichong Yin, Shuohuan Wang, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang:
ERNIE-UniX2: A Unified Cross-lingual Cross-modal Framework for Understanding and Generation. CoRR abs/2211.04861 (2022) - [i2]Bin Shan, Ye Li, Shengjun Huang:
VI-PINNs: Variance-involved Physics-informed Neural Networks for Fast and Accurate Prediction of Partial Differential Equations. CoRR abs/2211.16753 (2022) - [i1]Ye Li, Yiwen Pang, Bin Shan:
Physics-guided Data Augmentation for Learning the Solution Operator of Linear Differential Equations. CoRR abs/2212.04100 (2022)
Coauthor Index
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