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2020 – today
- 2024
[c13]Zijun Cui, Hanjing Wang, Tian Gao, Kartik Talamadupula, Qiang Ji:
Theory-guided Message Passing Neural Network for Probabilistic Inference. AISTATS 2024: 667-675- [c12]Hanjing Wang, Qiang Ji:
Epistemic Uncertainty Quantification for Pretrained Neural Networks. CVPR 2024: 11052-11061 - [c11]Hanjing Wang, Bashirul Azam Biswas, Qiang Ji
:
Optimization-Based Uncertainty Attribution Via Learning Informative Perturbations. ECCV (78) 2024: 237-253 - [c10]Hanjing Wang, Shiqiang Wang, Qiang Ji:
Semantic Attribution for Explainable Uncertainty Quantification. Epi UAI 2024: 101-112 - [i8]Hanjing Wang, Qiang Ji:
Epistemic Uncertainty Quantification For Pre-trained Neural Network. CoRR abs/2404.10124 (2024) - 2023
- [j2]Muning Wen, Runji Lin, Hanjing Wang, Yaodong Yang, Ying Wen, Luo Mai, Jun Wang, Hai-Feng Zhang, Weinan Zhang:
Large sequence models for sequential decision-making: a survey. Frontiers Comput. Sci. 17(6): 176349 (2023) - [j1]Ming Zhou, Ziyu Wan, Hanjing Wang, Muning Wen, Runzhe Wu, Ying Wen, Yaodong Yang, Yong Yu, Jun Wang, Weinan Zhang:
MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning. J. Mach. Learn. Res. 24: 150:1-150:12 (2023) - [c9]Hanjing Wang, Dhiraj Joshi, Shiqiang Wang, Qiang Ji:
Gradient-based Uncertainty Attribution for Explainable Bayesian Deep Learning. CVPR 2023: 12044-12053 - [c8]Yufei Zhang, Hanjing Wang, Jeffrey O. Kephart, Qiang Ji:
Body Knowledge and Uncertainty Modeling for Monocular 3D Human Body Reconstruction. ICCV 2023: 8986-8998 - [c7]Zhuo Huang, Hanjing Wang, Xinrui Shi:
The Future of Work: Do We Need Interactive Collaborative Offices? The Most Interesting Survey in a Post-Covid World. ICDCS Workshops 2023: 115-120 - [c6]Hanjing Wang, Man-Kit Sit, Congjie He, Ying Wen, Weinan Zhang, Jun Wang, Yaodong Yang, Luo Mai:
GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models. ICML 2023: 36380-36390 - [c5]Hanjing Wang, Qiang Ji:
Diversity-enhanced probabilistic ensemble for uncertainty estimation. UAI 2023: 2214-2225 - [i7]Hanjing Wang, Dhiraj Joshi, Shiqiang Wang, Qiang Ji:
Gradient-based Uncertainty Attribution for Explainable Bayesian Deep Learning. CoRR abs/2304.04824 (2023) - [i6]Muning Wen, Runji Lin, Hanjing Wang, Yaodong Yang, Ying Wen, Luo Mai, Jun Wang, Haifeng Zhang, Weinan Zhang:
Large Sequence Models for Sequential Decision-Making: A Survey. CoRR abs/2306.13945 (2023) - [i5]Yufei Zhang, Hanjing Wang, Jeffrey O. Kephart, Qiang Ji:
Body Knowledge and Uncertainty Modeling for Monocular 3D Human Body Reconstruction. CoRR abs/2308.00799 (2023) - [i4]Hanjing Wang, Man-Kit Sit, Congjie He, Ying Wen, Weinan Zhang, Jun Wang, Yaodong Yang, Luo Mai:
GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models. CoRR abs/2310.05205 (2023) - 2022
- [c4]Hongji Guo, Hanjing Wang, Qiang Ji:
Uncertainty-Guided Probabilistic Transformer for Complex Action Recognition. CVPR 2022: 20020-20029 - [c3]Zijun Cui, Hanjing Wang, Tian Gao, Kartik Talamadupula, Qiang Ji:
Variational message passing neural network for Maximum-A-Posteriori (MAP) inference. UAI 2022: 464-474 - 2021
- [i3]Ming Zhou, Ziyu Wan, Hanjing Wang, Muning Wen, Runzhe Wu, Ying Wen, Yaodong Yang, Weinan Zhang, Jun Wang:
MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning. CoRR abs/2106.07551 (2021) - 2020
- [c2]Fan Ding, Hanjing Wang, Ashish Sabharwal, Yexiang Xue:
Towards Efficient Discrete Integration via Adaptive Quantile Queries. ECAI 2020: 2577-2584
2010 – 2019
- 2019
- [c1]Yunfeng Lin, Jiangbei Li, Hanjing Wang:
DCNN-GAN: Reconstructing Realistic Image from fMRI. MVA 2019: 1-6 - [i2]Yunfeng Lin, Jiangbei Li, Hanjing Wang:
DCNN-GAN: Reconstructing Realistic Image from fMRI. CoRR abs/1901.07368 (2019) - [i1]Fan Ding, Hanjing Wang, Ashish Sabharwal, Yexiang Xue:
AdaWISH: Faster Discrete Integration via Adaptive Quantiles. CoRR abs/1910.05811 (2019)
Coauthor Index
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