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Xing Fu
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Title
Cited by
Cited by
Year
Multiresolution dynamic mode decomposition
JN Kutz, X Fu, SL Brunton
SIAM Journal on Applied Dynamical Systems 15 (2), 713-735, 2016
4052016
Multi-resolution dynamic mode decomposition for foreground/background separation and object tracking
JN Kutz, X Fu, SL Brunton, NB Erichson
2015 IEEE international conference on computer vision workshop (ICCVW), 921-929, 2015
692015
Self-tuning fiber lasers
SL Brunton, X Fu, JN Kutz
IEEE Journal of Selected Topics in Quantum Electronics 20 (5), 464-471, 2014
692014
Extremum-seeking control of a mode-locked laser
SL Brunton, X Fu, JN Kutz
IEEE Journal of Quantum Electronics 49 (10), 852-861, 2013
672013
Classification of birefringence in mode-locked fiber lasers using machine learning and sparse representation
X Fu, SL Brunton, JN Kutz
Optics express 22 (7), 8585-8597, 2014
582014
High-energy mode-locked fiber lasers using multiple transmission filters and a genetic algorithm
X Fu, JN Kutz
Optics express 21 (5), 6526-6537, 2013
492013
Self-tuning fiber lasers: machine learning applied to optical systems
JN Kutz, X Fu, S Brunton
Nonlinear Photonics, NTu4A. 7, 2014
92014
Differentially private learning with per-sample adaptive clipping
T Xia, S Shen, S Yao, X Fu, K Xu, X Xu, X Fu
Proceedings of the AAAI Conference on Artificial Intelligence 37 (9), 10444 …, 2023
62023
Multi-resolution time-scale separation of video content using the dynamic mode decomposition
J Kutz, J Grosek, X Fu, S Brunton
International Workshop on Video Processing and Quality Metrics for Consumer …, 2015
62015
Adaptive dimensionality-reduction for time-stepping in differential and partial differential equations
X Fu, JN Kutz
Numerical Mathematics: Theory, Methods and Applications 10 (4), 872-894, 2017
52017
Multi-resolution analysis of dynamical systems using dynamic mode decomposition
JN Kutz, S Brunton, X Fu
Proceedings of World Congress on Engineering 1, 1-3, 2015
52015
Machine learning for self-tuning optical systems
JN Kutz, SL Brunton
Nonlinear Optics, NTh1A. 1, 2019
42019
Using dynamic mode decomposition for real-time background/foreground separation in video
JN Kutz, J Grosek, S Brunton, X Fu, S Pendergrass
US Patent 9,674,406, 2017
42017
Data driven control of complex optical systems
SL Brunton, JN Kutz, X Fu, M Johnson
Nonlinear Optics, NW4A. 41, 2015
42015
Tuning multi-input complex dynamic systems using sparse representations of performance and extremum-seeking control
JN Kutz, S Brunton, X Fu
US Patent 9,972,962, 2018
32018
Using dynamic mode decomposition for real-time background/foreground separation in video
JN Kutz, J Grosek, S Brunton, X Fu, S Pendergrass
Univ. of Washington, Seattle, WA (United States), 2017
22017
Multi-resolution dynamic mode decomposition for foreground/background separation and object tracking
J Nathan Kutz, X Fu, SL Brunton, N Benjamin Erichson
Proceedings of the IEEE International Conference on Computer Vision …, 2015
22015
Multi-aspect heterogeneous graph augmentation
Y Zhou, Y Cao, Y Liu, Y Shang, P Zhang, Z Lin, Y Yue, B Wang, X Fu, ...
Proceedings of the ACM Web Conference 2023, 39-48, 2023
12023
Self-supervision meets kernel graph neural models: From architecture to augmentations
J Dan, R Wu, Y Liu, B Wang, C Meng, T Liu, T Zhang, N Wang, X Fu, Q Li, ...
2023 IEEE International Conference on Data Mining Workshops (ICDMW), 1076-1083, 2023
2023
A Momentum Loss Reweighting Method for Improving Recall
C Jiang, Y Jin, N Wang, R Wu, X Fu, W Wang
Proceedings of the 32nd ACM International Conference on Information and …, 2023
2023
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