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Yezhen Wang
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2020 – today
- 2024
- [i12]Yifei Shen, Xinyang Jiang, Yezhen Wang, Yifan Yang, Dongqi Han, Dongsheng Li:
Understanding Training-free Diffusion Guidance: Mechanisms and Limitations. CoRR abs/2403.12404 (2024) - [i11]Qianli Shen, Yezhen Wang, Zhouhao Yang, Xiang Li, Haonan Wang, Yang Zhang, Jonathan Scarlett, Zhanxing Zhu, Kenji Kawaguchi:
Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization. CoRR abs/2406.14095 (2024) - 2023
- [c9]Bo Li, Yifei Shen, Jingkang Yang, Yezhen Wang, Jiawei Ren, Tong Che, Jun Zhang, Ziwei Liu:
Sparse Mixture-of-Experts are Domain Generalizable Learners. ICLR 2023 - [i10]Zheyuan Hu
, Zhouhao Yang, Yezhen Wang, George Em Karniadakis, Kenji Kawaguchi:
Bias-Variance Trade-off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs. CoRR abs/2311.15283 (2023) - 2022
- [c8]Bo Li, Yifei Shen, Yezhen Wang, Wenzhen Zhu, Colorado Reed, Dongsheng Li, Kurt Keutzer, Han Zhao:
Invariant Information Bottleneck for Domain Generalization. AAAI 2022: 7399-7407 - [c7]Yiyuan Li, Tong Che, Yezhen Wang, Zhengbao Jiang, Caiming Xiong, Snigdha Chaturvedi:
SPE: Symmetrical Prompt Enhancement for Fact Probing. EMNLP 2022: 11689-11698 - [c6]Yezhen Wang:
An Improved k-Nearest Centroid Neighbor Classification Method for Incomplete Data. ICCSIE 2022: 869-873 - [i9]Bo Li, Jingkang Yang, Jiawei Ren, Yezhen Wang, Ziwei Liu:
Sparse Fusion Mixture-of-Experts are Domain Generalizable Learners. CoRR abs/2206.04046 (2022) - [i8]Yezhen Wang, Tong Che, Bo Li, Kaitao Song, Hengzhi Pei, Yoshua Bengio, Dongsheng Li:
Your Autoregressive Generative Model Can be Better If You Treat It as an Energy-Based One. CoRR abs/2206.12840 (2022) - [i7]Yiyuan Li, Tong Che, Yezhen Wang, Zhengbao Jiang, Caiming Xiong, Snigdha Chaturvedi:
SPE: Symmetrical Prompt Enhancement for Fact Probing. CoRR abs/2211.07078 (2022) - 2021
- [c5]Sicheng Zhao, Yezhen Wang, Bo Li, Bichen Wu, Yang Gao, Pengfei Xu, Trevor Darrell, Kurt Keutzer:
ePointDA: An End-to-End Simulation-to-Real Domain Adaptation Framework for LiDAR Point Cloud Segmentation. AAAI 2021: 3500-3509 - [c4]Bo Li, Yezhen Wang, Shanghang Zhang, Dongsheng Li, Kurt Keutzer, Trevor Darrell, Han Zhao:
Learning Invariant Representations and Risks for Semi-Supervised Domain Adaptation. CVPR 2021: 1104-1113 - [c3]Yatian Wang, Xiaolin Song
Dual Metric Discriminator for Open Set Video Domain Adaptation. ICASSP 2021: 8198-8202 - [c2]Yezhen Wang, Bo Li, Tong Che, Kaiyang Zhou, Ziwei Liu, Dongsheng Li:
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration. ICCV 2021: 9282-9291 - [i6]Bo Li, Yifei Shen, Yezhen Wang, Wenzhen Zhu, Colorado J. Reed, Jun Zhang, Dongsheng Li, Kurt Keutzer, Han Zhao:
Invariant Information Bottleneck for Domain Generalization. CoRR abs/2106.06333 (2021) - [i5]Yezhen Wang, Bo Li, Tong Che, Kaiyang Zhou, Ziwei Liu, Dongsheng Li:
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration. CoRR abs/2107.12628 (2021) - 2020
- [i4]Bo Li, Yezhen Wang, Tong Che, Shanghang Zhang, Sicheng Zhao, Pengfei Xu, Wei Zhou, Yoshua Bengio, Kurt Keutzer:
Rethinking Distributional Matching Based Domain Adaptation. CoRR abs/2006.13352 (2020) - [i3]Sicheng Zhao, Yezhen Wang, Bo Li, Bichen Wu, Yang Gao, Pengfei Xu, Trevor Darrell, Kurt Keutzer:
ePointDA: An End-to-End Simulation-to-Real Domain Adaptation Framework for LiDAR Point Cloud Segmentation. CoRR abs/2009.03456 (2020) - [i2]Bo Li, Yezhen Wang, Shanghang Zhang, Dongsheng Li, Trevor Darrell, Kurt Keutzer, Han Zhao:
Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation. CoRR abs/2010.04647 (2020)
2010 – 2019
- 2019
- [c1]Zhaoyi Yan, Yuchen Yuan, Wangmeng Zuo, Xiao Tan, Yezhen Wang, Shilei Wen, Errui Ding:
Perspective-Guided Convolution Networks for Crowd Counting. ICCV 2019: 952-961 - [i1]Zhaoyi Yan, Yuchen Yuan, Wangmeng Zuo, Xiao Tan, Yezhen Wang, Shilei Wen, Errui Ding:
Perspective-Guided Convolution Networks for Crowd Counting. CoRR abs/1909.06966 (2019)
Coauthor Index
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last updated on 2024-07-25 20:19 CEST by the dblp team
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