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ORCIDNing Chen 0002
Person information
- affiliation: Tsinghua University, TNList / Tsinghua-Fuzhou Institute for Data Technology, Beijing, China
Other persons with the same name
- Ning Chen — disambiguation page
- Ning Chen 0001 — InteliFusion Technologies, China (and 1 more)
- Ning Chen 0003
![[0000-0002-3153-8765]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-3153-8765")
— Henan Polytechnic University, College of Computer Science and Technology, China (and 1 more) - Ning Chen 0004 — Lehigh University, Department of Electrical and Computer Engineering, Bethlehem, PA, USA
- Ning Chen 0005 — Nanyang Technological University, Division of Mathematical Sciences, Singapore (and 1 more)
- Ning Chen 0006 — TU Munich, Institute for Electronic Design Automation, Germany
- Ning Chen 0007 — East China University of Science and Technology, School of Information Science & Engineering, Shanghai, China (and 1 more)
- Ning Chen 0008 — City University of Hong Kong, Hong Kong, SAR, China (and 2 more)
- Ning Chen 0009 — Central South University, School of Automation, Changsha, China
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2020 – today
- 2023
[c30]Xiao Yang, Chang Liu, Longlong Xu, Yikai Wang, Yinpeng Dong, Ning Chen, Hang Su, Jun Zhu:
Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition. CVPR 2023: 4119-4128- [c29]Shouwei Ruan, Yinpeng Dong, Hang Su, Jianteng Peng, Ning Chen, Xingxing Wei:
Towards Viewpoint-Invariant Visual Recognition via Adversarial Training. ICCV 2023: 4686-4696 - [i13]Xiao Yang, Chang Liu, Longlong Xu, Yikai Wang, Yinpeng Dong, Ning Chen, Hang Su, Jun Zhu:
Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition. CoRR abs/2303.15818 (2023) - [i12]Shouwei Ruan, Yinpeng Dong, Hang Su, Jianteng Peng, Ning Chen, Xingxing Wei:
Towards Viewpoint-Invariant Visual Recognition via Adversarial Training. CoRR abs/2307.10235 (2023) - [i11]Shouwei Ruan, Yinpeng Dong, Hang Su, Jianteng Peng, Ning Chen, Xingxing Wei:
Improving Viewpoint Robustness for Visual Recognition via Adversarial Training. CoRR abs/2307.11528 (2023) - 2022
- [j17]Wenkai Li, Wenbo Hu, Ting Chen, Ning Chen, Cheng Feng:
StackVAE-G: An efficient and interpretable model for time series anomaly detection. AI Open 3: 101-110 (2022) - [c28]Chengyang Ying, Xinning Zhou, Hang Su, Dong Yan, Ning Chen, Jun Zhu:
Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk. IJCAI 2022: 3673-3680 - [i10]Chengyang Ying, Xinning Zhou, Hang Su, Dong Yan, Ning Chen, Jun Zhu:
Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk. CoRR abs/2206.04436 (2022) - 2021
- [j16]Kaikun Xie, Zehua Liu, Ning Chen, Ting Chen:
redPATH: Reconstructing the Pseudo Development Time of Cell Lineages in Single-cell RNA-seq Data and Applications in Cancer. Genom. Proteom. Bioinform. 19(2): 292-305 (2021) - [j15]Yuqing Yang, Xin Wang, Kaikun Xie, Congmin Zhu, Ning Chen, Ting Chen:
kLDM: Inferring Multiple Metagenomic Association Networks Based on the Variation of Environmental Factors. Genom. Proteom. Bioinform. 19(5): 834-847 (2021) - [c27]Qingyi Pan, Wenbo Hu, Ning Chen:
Two Birds with One Stone: Series Saliency for Accurate and Interpretable Multivariate Time Series Forecasting. IJCAI 2021: 2884-2891 - [c26]Yunsheng Zhang, Dong Yan, Bei Shi, Haobo Fu, Qiang Fu, Hang Su, Jun Zhu, Ning Chen:
Combining Tree Search and Action Prediction for State-of-the-Art Performance in DouDiZhu. IJCAI 2021: 3413-3419 - [i9]Wenkai Li, Wenbo Hu, Ning Chen, Cheng Feng:
Stacking VAE with Graph Neural Networks for Effective and Interpretable Time Series Anomaly Detection. CoRR abs/2105.08397 (2021) - 2020
- [c25]Tianyu Pang, Kun Xu, Yinpeng Dong, Chao Du, Ning Chen, Jun Zhu:
Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness. ICLR 2020 - [c24]Ke Wang, Xuyan Chen, Ning Chen, Ting Chen:
Automatic Emergency Diagnosis with Knowledge-Based Tree Decoding. IJCAI 2020: 3407-3414 - [c23]Ke Wang, Ning Chen, Ting Chen:
Joint Medical Ontology Representation Learning for Healthcare Predictions. IJCNN 2020: 1-7
2010 – 2019
- 2019
- [j14]Yuqing Yang, Xin Wang, Yu Huang, Ning Chen, Juhong Shi, Ting Chen:
Ontology-based venous thromboembolism risk assessment model developing from medical records. BMC Medical Informatics Decis. Mak. 19-S(4): 151:1-151:13 (2019) - [j13]Ning Chen, Fuchun Sun, Linge Ding, Hongqiao Wang:
An adaptive PNN-DS approach to classification using multi-sensor information fusion. Neural Comput. Appl. 31(S-2): 693-705 (2019) - [c22]Ke Wang, Guangyu Wang, Ning Chen, Ting Chen:
How Robust is Your Automatic Diagnosis Model? BIBM 2019: 877-884 - [c21]Xiaohong Liu, Guangyu Wang, Yiming Xu, Ning Chen, Ting Chen:
Bone Age Assessment by Deep Convolutional Neural Networks Combined with Clinical TW3-RUS. BIBM 2019: 948-952 - [c20]Guangyu Wang, Xiaohong Liu, Ken Xie, Ning Chen, Ting Chen:
DeepTriager: A Neural Attention Model for Emergency Triage with Electronic Health Records. BIBM 2019: 978-982 - [c19]Yujuan Feng, Zhenxing Xu, Lin Gan, Ning Chen, Bin Yu, Ting Chen, Fei Wang:
DCMN: Double Core Memory Network for Patient Outcome Prediction with Multimodal Data. ICDM 2019: 200-209 - [c18]Xuan Zhang, Guangyu Wang, Ning Chen, Ting Chen:
Computer-aided Diagnosis of Ambulatory Electrocardiograms via ASRS: Active-Selection-Random-Selection. ICHI 2019: 1-9 - [c17]Tianyu Pang, Kun Xu, Chao Du, Ning Chen, Jun Zhu:
Improving Adversarial Robustness via Promoting Ensemble Diversity. ICML 2019: 4970-4979 - [i8]Tianyu Pang, Kun Xu, Chao Du, Ning Chen, Jun Zhu:
Improving Adversarial Robustness via Promoting Ensemble Diversity. CoRR abs/1901.08846 (2019) - [i7]Tianyu Pang, Kun Xu, Yinpeng Dong, Chao Du, Ning Chen, Jun Zhu:
Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness. CoRR abs/1905.10626 (2019) - 2018
- [j12]Ning Chen, Jun Zhu, Jianfei Chen, Ting Chen:
Dropout training for SVMs with data augmentation. Frontiers Comput. Sci. 12(4): 694-713 (2018) - [c16]Yuqing Yang, Xin Wang, Yu Huang, Ning Chen, Juhong Shi, Ting Chen:
Ontology-based Venous Thromboembolism Risk Factors Mining and Model Developing from Medical Records. BIBM 2018: 1669-1672 - [c15]Jingwei Zhuo, Chang Liu, Jiaxin Shi, Jun Zhu, Ning Chen, Bo Zhang:
Message Passing Stein Variational Gradient Descent. ICML 2018: 6013-6022 - 2017
- [j11]Linhao Jiang, Yichao Dong, Ning Chen, Ting Chen:
DACE: a scalable DP-means algorithm for clustering extremely large sequence data. Bioinform. 33(6): 834-842 (2017) - [j10]Xu Min, Wanwen Zeng, Ning Chen, Ting Chen, Rui Jiang:
Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding. Bioinform. 33(14): i92-i101 (2017) - [j9]Xu Min, Wanwen Zeng, Shengquan Chen, Ning Chen, Ting Chen, Rui Jiang:
Predicting enhancers with deep convolutional neural networks. BMC Bioinform. 18(S-13): 35-46 (2017) - [j8]Sai Zhang, Muxuan Liang, Zhongjun Zhou, Chen Zhang, Ning Chen, Ting Chen, Jianyang Zeng:
Elastic restricted Boltzmann machines for cancer data analysis. Quant. Biol. 5(2): 159-172 (2017) - [c14]Tian Tian, Ning Chen, Jun Zhu:
Learning Attributes from the Crowdsourced Relative Labels. AAAI 2017: 1562-1568 - [c13]Yujuan Feng, Xu Min, Ning Chen, Hu Chen, Xiaolei Xie, Haibo Wang, Ting Chen:
Patient outcome prediction via convolutional neural networks based on multi-granularity medical concept embedding. BIBM 2017: 770-777 - 2016
- [c12]Bei Chen, Ning Chen, Jun Zhu, Jiaming Song, Bo Zhang:
Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation. AAAI 2016: 1153-1159 - [c11]Xu Min, Ning Chen, Ting Chen, Rui Jiang:
DeepEnhancer: Predicting enhancers by convolutional neural networks. BIBM 2016: 637-644 - [c10]Yuqing Yang, Ning Chen, Ting Chen:
mLDM: A New Hierarchical Bayesian Statistical Model for Sparse Microbial Association Discovery. RECOMB 2016: 253-254 - 2015
- [j7]Ning Chen, Jun Zhu, Fei Xia, Bo Zhang:
Discriminative Relational Topic Models. IEEE Trans. Pattern Anal. Mach. Intell. 37(5): 973-986 (2015) - [i6]Ning Chen, Jun Zhu, Jianfei Chen, Ting Chen:
Dropout Training for SVMs with Data Augmentation. CoRR abs/1508.02268 (2015) - [i5]Bei Chen, Ning Chen, Jun Zhu, Jiaming Song, Bo Zhang:
Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation. CoRR abs/1512.02016 (2015) - 2014
- [j6]Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang:
Gibbs max-margin topic models with data augmentation. J. Mach. Learn. Res. 15(1): 1073-1110 (2014) - [j5]Jun Zhu, Ning Chen, Eric P. Xing:
Bayesian inference with posterior regularization and applications to infinite latent SVMs. J. Mach. Learn. Res. 15(1): 1799-1847 (2014) - [j4]Ning Chen, Jun Zhu, Fuchun Sun, Bo Zhang:
Learning Harmonium Models With Infinite Latent Features. IEEE Trans. Neural Networks Learn. Syst. 25(3): 520-532 (2014) - [c9]Ning Chen, Jun Zhu, Jianfei Chen, Bo Zhang:
Dropout Training for Support Vector Machines. AAAI 2014: 1752-1759 - [c8]Fei Xia, Ning Chen, Jun Zhu, Aonan Zhang, Xiaoming Jin:
Max-margin latent feature relational models for entity-attribute networks. IJCNN 2014: 1667-1674 - [i4]Ning Chen, Jun Zhu, Jianfei Chen, Bo Zhang:
Dropout Training for Support Vector Machines. CoRR abs/1404.4171 (2014) - 2013
- [c7]Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang:
Gibbs Max-Margin Topic Models with Fast Sampling Algorithms. ICML (1) 2013: 124-132 - [c6]Ning Chen, Jun Zhu, Fei Xia, Bo Zhang:
Generalized Relational Topic Models with Data Augmentation. IJCAI 2013: 1273-1279 - [i3]Ning Chen, Jun Zhu, Fei Xia, Bo Zhang:
Discriminative Relational Topic Models. CoRR abs/1310.2409 (2013) - [i2]Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang:
Gibbs Max-margin Topic Models with Data Augmentation. CoRR abs/1310.2816 (2013) - 2012
- [j3]Ning Chen, Jun Zhu, Fuchun Sun, Eric P. Xing:
Large-Margin Predictive Latent Subspace Learning for Multiview Data Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 34(12): 2365-2378 (2012) - [i1]Jun Zhu, Ning Chen, Eric P. Xing:
Bayesian Inference with Posterior Regularization and Infinite Latent Support Vector Machines. CoRR abs/1210.1766 (2012) - 2011
- [c5]Jun Zhu, Ning Chen, Eric P. Xing:
Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines. ICML 2011: 617-624 - [c4]Jun Zhu, Ni Lao, Ning Chen, Eric P. Xing:
Conditional topical coding: an efficient topic model conditioned on rich features. KDD 2011: 475-483 - [c3]Jun Zhu, Ning Chen, Eric P. Xing:
Infinite Latent SVM for Classification and Multi-task Learning. NIPS 2011: 1620-1628 - 2010
- [j2]Hongqiao Wang, Fuchun Sun, Yan-Ning Cai, Linge Ding, Ning Chen:
An unbiased LSSVM model for classification and regression. Soft Comput. 14(2): 171-180 (2010) - [c2]Ning Chen, Jun Zhu, Eric P. Xing:
Predictive Subspace Learning for Multi-view Data: a Large Margin Approach. NIPS 2010: 361-369
2000 – 2009
- 2009
- [j1]Ning Chen, Fuchun Sun, Linge Ding, Hongqiao Wang:
An adaptive PNN-DS approach to classification using multi-sensor information fusion. Neural Comput. Appl. 18(5): 455-467 (2009) - 2008
- [c1]Linge Ding, Fuchun Sun, Hongqiao Wang, Ning Chen:
A Sparse Sampling Method for Classification Based on Likelihood Factor. ISNN (2) 2008: 268-275
Coauthor Index
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