Ning Chen - RankMe

61 papers A* 17B 3Journal 30Unranked 11

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Improving Viewpoint Robustness for Visual Recognition via Adversarial Training. CoRR Shouwei Ruan, Yinpeng Dong, Hang Su, Jianteng Peng, Ning Chen, Xingxing Wei
2023	A*	`conf`	Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition. CVPR Xiao Yang, Chang Liu, Longlong Xu, Yikai Wang, Yinpeng Dong, Ning Chen, Hang Su, Jun Zhu
2023	J	`jnl`	Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition. CoRR Xiao Yang, Chang Liu, Longlong Xu, Yikai Wang, Yinpeng Dong, Ning Chen, Hang Su, Jun Zhu
2023	A*	`conf`	Towards Viewpoint-Invariant Visual Recognition via Adversarial Training. ICCV Shouwei Ruan, Yinpeng Dong, Hang Su, Jianteng Peng, Ning Chen, Xingxing Wei
2023	J	`jnl`	Towards Viewpoint-Invariant Visual Recognition via Adversarial Training. CoRR Shouwei Ruan, Yinpeng Dong, Hang Su, Jianteng Peng, Ning Chen, Xingxing Wei
2022	J	`jnl`	StackVAE-G: An efficient and interpretable model for time series anomaly detection. AI Open Wenkai Li, Wenbo Hu, Ting Chen, Ning Chen, Cheng Feng
2022	A*	`conf`	Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk. IJCAI Chengyang Ying, Xinning Zhou, Hang Su, Dong Yan, Ning Chen, Jun Zhu
2022	J	`jnl`	Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk. CoRR Chengyang Ying, Xinning Zhou, Hang Su, Dong Yan, Ning Chen, Jun Zhu
2021	A*	`conf`	Combining Tree Search and Action Prediction for State-of-the-Art Performance in DouDiZhu. IJCAI Yunsheng Zhang, Dong Yan, Bei Shi, Haobo Fu, Qiang Fu, Hang Su, Jun Zhu, Ning Chen
2021	J	`jnl`	Stacking VAE with Graph Neural Networks for Effective and Interpretable Time Series Anomaly Detection. CoRR Wenkai Li, Wenbo Hu, Ning Chen, Cheng Feng
2021	A*	`conf`	Two Birds with One Stone: Series Saliency for Accurate and Interpretable Multivariate Time Series Forecasting. IJCAI Qingyi Pan, Wenbo Hu, Ning Chen
2021	J	`jnl`	kLDM: Inferring Multiple Metagenomic Association Networks Based on the Variation of Environmental Factors. Genom. Proteom. Bioinform. Yuqing Yang, Xin Wang, Kaikun Xie, Congmin Zhu, Ning Chen, Ting Chen
2021	J	`jnl`	redPATH: Reconstructing the Pseudo Development Time of Cell Lineages in Single-cell RNA-seq Data and Applications in Cancer. Genom. Proteom. Bioinform. Kaikun Xie, Zehua Liu, Ning Chen, Ting Chen
2020	A*	`conf`	Automatic Emergency Diagnosis with Knowledge-Based Tree Decoding. IJCAI Ke Wang, Xuyan Chen, Ning Chen, Ting Chen
2020	B	`conf`	Joint Medical Ontology Representation Learning for Healthcare Predictions. IJCNN Ke Wang, Ning Chen, Ting Chen
2020	A*	`conf`	Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness. ICLR Tianyu Pang, Kun Xu, Yinpeng Dong, Chao Du, Ning Chen, Jun Zhu
2019	J	`jnl`	An adaptive PNN-DS approach to classification using multi-sensor information fusion. Neural Comput. Appl. Ning Chen, Fuchun Sun, Linge Ding, Hongqiao Wang
2019	—	`conf`	Bone Age Assessment by Deep Convolutional Neural Networks Combined with Clinical TW3-RUS. BIBM Xiaohong Liu, Guangyu Wang, Yiming Xu, Ning Chen, Ting Chen
2019	—	`conf`	Computer-aided Diagnosis of Ambulatory Electrocardiograms via ASRS: Active-Selection-Random-Selection. ICHI Xuan Zhang, Guangyu Wang, Ning Chen, Ting Chen
2019	A*	`conf`	DCMN: Double Core Memory Network for Patient Outcome Prediction with Multimodal Data. ICDM Yujuan Feng, Zhenxing Xu, Lin Gan, Ning Chen, Bin Yu, Ting Chen, Fei Wang
2019	—	`conf`	DeepTriager: A Neural Attention Model for Emergency Triage with Electronic Health Records. BIBM Guangyu Wang, Xiaohong Liu, Ken Xie, Ning Chen, Ting Chen
2019	—	`conf`	How Robust is Your Automatic Diagnosis Model? BIBM Ke Wang, Guangyu Wang, Ning Chen, Ting Chen
2019	A*	`conf`	Improving Adversarial Robustness via Promoting Ensemble Diversity. ICML Tianyu Pang, Kun Xu, Chao Du, Ning Chen, Jun Zhu
2019	J	`jnl`	Improving Adversarial Robustness via Promoting Ensemble Diversity. CoRR Tianyu Pang, Kun Xu, Chao Du, Ning Chen, Jun Zhu
2019	J	`jnl`	Ontology-based venous thromboembolism risk assessment model developing from medical records. BMC Medical Informatics Decis. Mak. Yuqing Yang, Xin Wang, Yu Huang, Ning Chen, Juhong Shi, Ting Chen
2019	J	`jnl`	Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness. CoRR Tianyu Pang, Kun Xu, Yinpeng Dong, Chao Du, Ning Chen, Jun Zhu
2019	A*	`conf`	Transferable Adversarial Attacks for Image and Video Object Detection. IJCAI Xingxing Wei, Siyuan Liang, Ning Chen, Xiaochun Cao
2018	J	`jnl`	Dropout training for SVMs with data augmentation. Frontiers Comput. Sci. Ning Chen, Jun Zhu, Jianfei Chen, Ting Chen
2018	A*	`conf`	Message Passing Stein Variational Gradient Descent. ICML Jingwei Zhuo, Chang Liu, Jiaxin Shi, Jun Zhu, Ning Chen, Bo Zhang
2018	—	`conf`	Ontology-based Venous Thromboembolism Risk Factors Mining and Model Developing from Medical Records. BIBM Yuqing Yang, Xin Wang, Yu Huang, Ning Chen, Juhong Shi, Ting Chen
2017	J	`jnl`	Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding. Bioinform. Xu Min, Wanwen Zeng, Ning Chen, Ting Chen, Rui Jiang
2017	J	`jnl`	DACE: a scalable DP-means algorithm for clustering extremely large sequence data. Bioinform. Linhao Jiang, Yichao Dong, Ning Chen, Ting Chen
2017	J	`jnl`	Elastic restricted Boltzmann machines for cancer data analysis. Quant. Biol. Sai Zhang, Muxuan Liang, Zhongjun Zhou, Chen Zhang, Ning Chen, Ting Chen, Jianyang Zeng
2017	A*	`conf`	Learning Attributes from the Crowdsourced Relative Labels. AAAI Tian Tian, Ning Chen, Jun Zhu
2017	—	`conf`	Patient outcome prediction via convolutional neural networks based on multi-granularity medical concept embedding. BIBM Yujuan Feng, Xu Min, Ning Chen, Hu Chen, Xiaolei Xie, Haibo Wang, Ting Chen
2017	J	`jnl`	Predicting enhancers with deep convolutional neural networks. BMC Bioinform. Xu Min, Wanwen Zeng, Shengquan Chen, Ning Chen, Ting Chen, Rui Jiang
2016	—	`conf`	DeepEnhancer: Predicting enhancers by convolutional neural networks. BIBM Xu Min, Ning Chen, Ting Chen, Rui Jiang
2016	A*	`conf`	Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation. AAAI Bei Chen, Ning Chen, Jun Zhu, Jiaming Song, Bo Zhang
2016	B	`conf`	mLDM: A New Hierarchical Bayesian Statistical Model for Sparse Microbial Association Discovery. RECOMB Yuqing Yang, Ning Chen, Ting Chen
2015	J	`jnl`	Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation. CoRR Bei Chen, Ning Chen, Jun Zhu, Jiaming Song, Bo Zhang
2015	J	`jnl`	Discriminative Relational Topic Models. IEEE Trans. Pattern Anal. Mach. Intell. Ning Chen, Jun Zhu, Fei Xia, Bo Zhang
2015	J	`jnl`	Dropout Training for SVMs with Data Augmentation. CoRR Ning Chen, Jun Zhu, Jianfei Chen, Ting Chen
2014	J	`jnl`	Bayesian inference with posterior regularization and applications to infinite latent SVMs. J. Mach. Learn. Res. Jun Zhu, Ning Chen, Eric P. Xing
2014	A*	`conf`	Dropout Training for Support Vector Machines. AAAI Ning Chen, Jun Zhu, Jianfei Chen, Bo Zhang
2014	J	`jnl`	Dropout Training for Support Vector Machines. CoRR Ning Chen, Jun Zhu, Jianfei Chen, Bo Zhang
2014	J	`jnl`	Gibbs max-margin topic models with data augmentation. J. Mach. Learn. Res. Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang
2014	J	`jnl`	Learning Harmonium Models With Infinite Latent Features. IEEE Trans. Neural Networks Learn. Syst. Ning Chen, Jun Zhu, Fuchun Sun, Bo Zhang
2014	B	`conf`	Max-margin latent feature relational models for entity-attribute networks. IJCNN Fei Xia, Ning Chen, Jun Zhu, Aonan Zhang, Xiaoming Jin
2013	J	`jnl`	Discriminative Relational Topic Models. CoRR Ning Chen, Jun Zhu, Fei Xia, Bo Zhang
2013	A*	`conf`	Generalized Relational Topic Models with Data Augmentation. IJCAI Ning Chen, Jun Zhu, Fei Xia, Bo Zhang
2013	—	`conf`	Gibbs Max-Margin Topic Models with Fast Sampling Algorithms. ICML (1) Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang
2013	J	`jnl`	Gibbs Max-margin Topic Models with Data Augmentation. CoRR Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang
2012	J	`jnl`	Bayesian Inference with Posterior Regularization and Infinite Latent Support Vector Machines CoRR Jun Zhu, Ning Chen, Eric P. Xing
2012	J	`jnl`	Large-Margin Predictive Latent Subspace Learning for Multiview Data Analysis. IEEE Trans. Pattern Anal. Mach. Intell. Ning Chen, Jun Zhu, Fuchun Sun, Eric P. Xing
2011	A*	`conf`	Conditional topical coding: an efficient topic model conditioned on rich features. KDD Jun Zhu, Ni Lao, Ning Chen, Eric P. Xing
2011	—	`conf`	Infinite Latent SVM for Classification and Multi-task Learning. NIPS Jun Zhu, Ning Chen, Eric P. Xing
2011	A*	`conf`	Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines. ICML Jun Zhu, Ning Chen, Eric P. Xing
2010	J	`jnl`	An unbiased LSSVM model for classification and regression. Soft Comput. Hongqiao Wang, Fuchun Sun, Yan-Ning Cai, Linge Ding, Ning Chen
2010	—	`conf`	Predictive Subspace Learning for Multi-view Data: a Large Margin Approach. NIPS Ning Chen, Jun Zhu, Eric P. Xing
2009	J	`jnl`	An adaptive PNN-DS approach to classification using multi-sensor information fusion. Neural Comput. Appl. Ning Chen, Fuchun Sun, Linge Ding, Hongqiao Wang
2008	—	`conf`	A Sparse Sampling Method for Classification Based on Likelihood Factor. ISNN (2) Linge Ding, Fuchun Sun, Hongqiao Wang, Ning Chen