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Li Bo
Li Bo
Phd Student, NTU, Singapore
Verified email at e.ntu.edu.sg - Homepage
Title
Cited by
Cited by
Year
Multi-source domain adaptation for semantic segmentation
S Zhao, B Li, X Yue, Y Gu, P Xu, R Hu, H Chai, K Keutzer
NeurIPS 2019, 2019
992019
A review of single-source deep unsupervised visual domain adaptation
S Zhao, X Yue, S Zhang, B Li, H Zhao, B Wu, R Krishna, JE Gonzalez, ...
IEEE Transactions on Neural Networks and Learning Systems, 2020
662020
Multi-source domain adaptation in the deep learning era: A systematic survey
S Zhao, B Li, P Xu, K Keutzer
arXiv preprint arXiv:2002.12169, 2020
472020
Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation
B Li, Y Wang, S Zhang, D Li, T Darrell, K Keutzer, H Zhao
CVPR 2021, 2020
252020
ePointDA: An End-to-End Simulation-to-Real Domain Adaptation Framework for LiDAR Point Cloud Segmentation
S Zhao, Y Wang, B Li, B Wu, Y Gao, P Xu, T Darrell, K Keutzer
AAAI 2021, 2020
242020
Self-Supervised Pretraining Improves Self-Supervised Pretraining
CJ Reed, X Yue, A Nrusimha, S Ebrahimi, V Vijaykumar, R Mao, B Li, ...
WACV 2022, 2021
232021
Rethinking distributional matching based domain adaptation
B Li, Y Wang, T Che, S Zhang, S Zhao, P Xu, W Zhou, Y Bengio, ...
arXiv preprint arXiv:2006.13352, 2020
222020
MADAN: multi-source adversarial domain aggregation network for domain adaptation
S Zhao, B Li, P Xu, X Yue, G Ding, K Keutzer
International Journal of Computer Vision 129 (8), 2399-2424, 2021
192021
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
Y Wang, B Li, T Che, K Zhou, D Li, Z Liu
ICCV 2021, 2021
62021
Invariant Information Bottleneck for Domain Generalization
B Li, Y Shen, Y Wang, W Zhu, CJ Reed, D Li, K Keutzer, H Zhao
AAAI 2022, 2021
32021
Domain generalization using pretrained models without fine-tuning
Z Li, K Ren, X Jiang, B Li, H Zhang, D Li
arXiv preprint arXiv:2203.04600, 2022
22022
Full-Cycle Energy Consumption Benchmark for Low-Carbon Computer Vision
B Li, X Jiang, D Bai, Y Zhang, N Zheng, X Dong, L Liu, Y Yang, D Li
arXiv preprint arXiv:2108.13465, 2021
22021
Sparse Fusion Mixture-of-Experts are Domain Generalizable Learners
B Li, J Yang, J Ren, Y Wang, Z Liu
arXiv preprint arXiv:2206.04046, 2022
2022
Your Autoregressive Generative Model Can be Better If You Treat It as an Energy-Based One
Y Wang, T Che, B Li, K Song, H Pei, Y Bengio, D Li
Preprint, 2022
2022
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