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ORCIDPengfei Yang 0002
Person information
- affiliation: Chinese Academy of Sciences, Institute of Software, Beijing, China
- affiliation: University of Chinese Academy of Sciences, Beijing, China
Other persons with the same name
- Pengfei Yang — disambiguation page
- Pengfei Yang 0001
![[0000-0003-4065-4052]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0003-4065-4052")
— Xidian University, School of Computer Science and Technology, Xi'an, China - Pengfei Yang 0003 — Point72 Asset Management, L.P., New York, NY, USA (and 1 more)
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2020 – today
- 2024
[c11]Jianan Ma, Pengfei Yang, Jingyi Wang, Youcheng Sun, Cheng-Chao Huang, Zhen Wang:
VeRe: Verification Guided Synthesis for Repairing Deep Neural Networks. ICSE 2024: 8:1-8:13- [c10]Zongxin Liu, Pengfei Yang, Lijun Zhang, Xiaowei Huang:
DeepCDCL: A CDCL-based Neural Network Verification Framework. TASE 2024: 343-355 - [i12]Zongxin Liu, Pengfei Yang, Lijun Zhang, Xiaowei Huang:
DeepCDCL: An CDCL-based Neural Network Verification Framework. CoRR abs/2403.07956 (2024) - [i11]Zhiming Chi, Jianan Ma, Pengfei Yang, Cheng-Chao Huang, Renjue Li, Xiaowei Huang, Lijun Zhang:
ADVREPAIR: Provable Repair of Adversarial Attack. CoRR abs/2404.01642 (2024) - 2023
- [c9]Liang Zhang, Nathaniel Xu, Pengfei Yang, Gaojie Jin, Cheng-Chao Huang, Lijun Zhang:
TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models. ICCV 2023: 8293-8305 - [i10]Pengfei Yang, Zhiming Chi, Zongxin Liu, Mengyu Zhao, Cheng-Chao Huang, Shaowei Cai, Lijun Zhang:
Incremental Satisfiability Modulo Theory for Verification of Deep Neural Networks. CoRR abs/2302.06455 (2023) - [i9]Liang Zhang, Nathaniel Xu, Pengfei Yang, Gaojie Jin, Cheng-Chao Huang, Lijun Zhang:
TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models. CoRR abs/2308.05985 (2023) - 2022
- [j3]Gaojie Jin, Xinping Yi, Pengfei Yang, Lijun Zhang, Sven Schewe, Xiaowei Huang:
Weight Expansion: A New Perspective on Dropout and Generalization. Trans. Mach. Learn. Res. 2022 (2022) - [c8]Renjue Li, Pengfei Yang, Cheng-Chao Huang, Youcheng Sun, Bai Xue, Lijun Zhang:
Towards Practical Robustness Analysis for DNNs based on PAC-Model Learning. ICSE 2022: 2189-2201 - [i8]Gaojie Jin, Xinping Yi, Pengfei Yang, Lijun Zhang, Sven Schewe, Xiaowei Huang:
Weight Expansion: A New Perspective on Dropout and Generalization. CoRR abs/2201.09209 (2022) - [i7]Depeng Liu, Lutan Zhao, Pengfei Yang, Bow-Yaw Wang, Rui Hou, Lijun Zhang, Naijun Zhan:
Defensive Design of Saturating Counters Based on Differential Privacy. CoRR abs/2206.00279 (2022) - [i6]Renjue Li, Tianhang Qin, Pengfei Yang, Cheng-Chao Huang, Youcheng Sun, Lijun Zhang:
Safety Analysis of Autonomous Driving Systems Based on Model Learning. CoRR abs/2211.12733 (2022) - 2021
- [j2]Pengfei Yang, Jianlin Li, Jiangchao Liu, Cheng-Chao Huang, Renjue Li, Liqian Chen, Xiaowei Huang, Lijun Zhang:
Enhancing Robustness Verification for Deep Neural Networks via Symbolic Propagation. Formal Aspects Comput. 33(3): 407-435 (2021) - [c7]Pengfei Yang, Renjue Li, Jianlin Li, Cheng-Chao Huang, Jingyi Wang, Jun Sun, Bai Xue, Lijun Zhang:
Improving Neural Network Verification through Spurious Region Guided Refinement. TACAS (1) 2021: 389-408 - [i5]Renjue Li, Pengfei Yang, Cheng-Chao Huang, Bai Xue, Lijun Zhang:
Probabilistic Robustness Analysis for DNNs based on PAC Learning. CoRR abs/2101.10102 (2021) - [i4]Renjue Li, Hanwei Zhang, Pengfei Yang, Cheng-Chao Huang, Aimin Zhou, Bai Xue, Lijun Zhang:
Ensemble Defense with Data Diversity: Weak Correlation Implies Strong Robustness. CoRR abs/2106.02867 (2021) - 2020
- [c6]Weipeng Cao, Pengfei Yang, Zhong Ming, Shubin Cai, Jiyong Zhang:
An Improved Fuzziness based Random Vector Functional Link Network for Liver Disease Detection. BigDataSecurity/HPSC/IDS 2020: 42-48 - [c5]David N. Jansen, Jan Friso Groote, Ferry Timmers, Pengfei Yang:
A Near-Linear-Time Algorithm for Weak Bisimilarity on Markov Chains. CONCUR 2020: 8:1-8:20 - [c4]Renjue Li, Jianlin Li, Cheng-Chao Huang, Pengfei Yang, Xiaowei Huang, Lijun Zhang, Bai Xue, Holger Hermanns:
PRODeep: a platform for robustness verification of deep neural networks. ESEC/SIGSOFT FSE 2020: 1630-1634 - [i3]Pengfei Yang, Renjue Li, Jianlin Li, Cheng-Chao Huang, Jingyi Wang, Jun Sun, Bai Xue, Lijun Zhang:
Improving Neural Network Verification through Spurious Region Guided Refinement. CoRR abs/2010.07722 (2020)
2010 – 2019
- 2019
- [c3]Weipeng Cao, Muhammed J. A. Patwary, Pengfei Yang, Xizhao Wang, Zhong Ming:
An Initial Study on the Relationship Between Meta Features of Dataset and the Initialization of NNRW. IJCNN 2019: 1-8 - [c2]Jianlin Li, Jiangchao Liu, Pengfei Yang, Liqian Chen, Xiaowei Huang, Lijun Zhang:
Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification. SAS 2019: 296-319 - [i2]Pengfei Yang, Jiangchao Liu, Jianlin Li, Liqian Chen, Xiaowei Huang:
Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification. CoRR abs/1902.09866 (2019) - 2018
- [j1]Lijun Zhang, Pengfei Yang, Lei Song, Holger Hermanns, Christian Eisentraut, David N. Jansen, Jens Chr. Godskesen:
Probabilistic bisimulation for realistic schedulers. Acta Informatica 55(6): 461-488 (2018) - 2017
- [c1]Pengfei Yang, David N. Jansen, Lijun Zhang:
Distribution-Based Bisimulation for Labelled Markov Processes. FORMATS 2017: 170-186 - [i1]Pengfei Yang, David N. Jansen, Lijun Zhang:
Distribution-based bisimulation for labelled Markov processes. CoRR abs/1706.10049 (2017)
Coauthor Index
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