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Lanqing HONG
Lanqing HONG
National University of Singapore, Huawei Noah's Ark Lab
在 u.nus.edu 的电子邮件经过验证
标题
引用次数
引用次数
年份
Thinning ferroelectric films for high-efficiency photovoltaics based on the Schottky barrier effect
Z Tan, L Hong, Z Fan, J Tian, L Zhang, Y Jiang, Z Hou, D Chen, M Qin, ...
NPG Asia Materials 11 (1), 1-13, 2019
452019
When is acceleration unnecessary in a degradation test?
L Hong, Z Ye
Statistica Sinica, 1461-1483, 2017
402017
A random-effects Wiener degradation model based on accelerated failure time
Q Zhai, P Chen, L Hong, L Shen
Reliability Engineering & System Safety 180, 94-103, 2018
392018
An artificial optoelectronic synapse based on a photoelectric memcapacitor
L Zhao, Z Fan, S Cheng, L Hong, Y Li, G Tian, D Chen, Z Hou, M Qin, ...
Advanced Electronic Materials 6 (2), 1900858, 2020
372020
OOD-Bench: Quantifying and Understanding Two Dimensions of Out-of-Distribution Generalization
N Ye, K Li, H Bai, R Yu, L Hong, F Zhou, Z Li, J Zhu
Computer Vision and Pattern Recognition (CVPR), 2022
29*2022
DecAug: Out-of-distribution generalization via decomposed feature representation and semantic augmentation
H Bai, R Sun, L Hong, F Zhou, N Ye, HJ Ye, SHG Chan, Z Li
AAAI Conference on Artificial Intelligence (AAAI), 2021
212021
SODA10M: A Large-Scale 2D Self/Semi-Supervised Object Detection Dataset for Autonomous Driving
J Han, X Liang, H Xu, K Chen, L Hong, C Ye, W Zhang, Z Li, X Liang, ...
NeurIPS 2021 Datasets and Benchmarks Track, 2021
20*2021
Interval estimation for Wiener processes based on accelerated degradation test data
L Hong, ZS Ye, J Kartika Sari
IISE Transactions 50 (12), 1043-1057, 2018
202018
System reliability evaluation under dynamic operating conditions
L Hong, Q Zhai, X Wang, ZS Ye
IEEE Transactions on Reliability 68 (3), 800-809, 2018
202018
Test-Agnostic Long-Tailed Recognition by Test-Time Aggregating Diverse Experts with Self-Supervision
Y Zhang, B Hooi, L Hong, J Feng
Neural Information Processing Systems (NeurIPS), 2021
192021
MultiSiam: Self-supervised multi-instance siamese representation learning for autonomous driving
K Chen, L Hong, H Xu, Z Li, DY Yeung
International Conference on Computer Vision (ICCV), 7546-7554, 2021
182021
Highly controllable and silicon-compatible ferroelectric photovoltaic synapses for neuromorphic computing
S Cheng, Z Fan, J Rao, L Hong, Q Huang, R Tao, Z Hou, M Qin, M Zeng, ...
iScience 23 (12), 101874, 2020
182020
An electroforming-free, analog interface-type memristor based on a SrFeOx epitaxial heterojunction for neuromorphic computing
J Rao, Z Fan, L Hong, S Cheng, Q Huang, J Zhao, X Xiang, EJ Guo, ...
Materials Today Physics 18, 100392, 2021
172021
OrdisCo: Effective and efficient usage of incremental unlabeled data for semi-supervised continual learning
L Wang, K Yang, C Li, L Hong, Z Li, J Zhu
Computer Vision and Pattern Recognition (CVPR), 5383-5392, 2021
162021
Adversarial robustness for unsupervised domain adaptation
M Awais, F Zhou, H Xu, L Hong, P Luo, SH Bae, Z Li
International Conference on Computer Vision (ICCV), 8568-8577, 2021
142021
Degradation-based reliability modeling of complex systems in dynamic environments
W Peng, L Hong, Z Ye
Statistical modeling for degradation data, 81-103, 2017
112017
NAS-OOD: Neural architecture search for out-of-distribution generalization
H Bai, F Zhou, L Hong, N Ye, SHG Chan, Z Li
International Conference on Computer Vision (ICCV), 8320-8329, 2021
82021
How Well Self-Supervised Pre-Training Performs with Streaming Data?
D Hu, Q Lu, L Hong, H Hu, Y Zhang, Z Li, J Feng
International Conference on Learning Representations (ICLR), 2022
72022
MetaAugment: Sample-Aware Data Augmentation Policy Learning
F Zhou, J Li, C Xie, F Chen, L Hong, R Sun, Z Li
AAAI Conference on Artificial Intelligence (AAAI), 2021
72021
Environmental risk assessment of emerging contaminants using degradation data
L Hong, ZS Ye, R Ling
Journal of Agricultural, Biological and Environmental Statistics 23 (3), 390-409, 2018
72018
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