1. Yuxin Li, Wenchao Chen , Xinyue Hu , Bo Chen* , Dongsheng Wang , Chunhui Qu, Fei Meng, Penghui Wang, and Hongwei Liu, AOT: Aggregation Optimal Transport for Few-Shot SAR Automatic Target Recognition, to appear in IEEE Transactions on Aerospace and Electronic Systems, 2024. 
2. Guanliang Liu, Wenchao Chen, Bo Chen*, Bo Feng, Penghui Wang and Hongwei Liu, Supervised Contrastive Deep Q-Network for Imbalanced Radar Automatic Target Recognition, to appear in Pattern Recognition, 2024. 
3. Yuxin Li, Yaoxuan Feng, Wenchao Chen, Yubiao Wang, Xinyue Hu, Baolin Sun, Chunhui Qu, Bo Chen*, and Mingyuan Zhou, Vague Prototype-Oriented Diffusion Model for Multi-Class Anomaly Detection, to appear in International Conference on Machine Learning (ICML), Vienna, Austria, July 2024.
4. Jianqiao Sun, Bo Chen*, Ruiying Lu, Ziheng Cheng, Chunhui Qu, and Xin Yuan, Advancing Hyperspectral and Multispectral Image Fusion: An Information-aware Transformer-based Unfolding Network, to appear in IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
5. Xinyang Liu, Dongsheng Wang, Bowei Fang, Miaoge Li, Yishi Xu, Zhibin Duan, Bo Chen*, and Mingyuan Zhou, Patch-Prompt Aligned Bayesian Prompt Tuning for Vision-Language Models, to appear in the Conference on Uncertainty in Artificial Intelligence (UAI), Barcelona, Spain, 2024.
6. Ruiying Lu, Ziheng Cheng, Bo Chen*, and Xin Yuan*, Motion-aware Dynamic Graph Neural Network for Video Compressive Sensing, to appear in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
7. Yuxin Li, Wenchao Chen, Xinyue Hu, Bo Chen*, baolin sun, Mingyuan Zhou, Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting, to appear in International Conference on Learning Representations (ICLR), Vienna, Austria, May 2024.
8. Yishi Xu, Jianqiao Sun, Yudi Su, Xinyang Liu, Zhibin Duan, Bo Chen* and Mingyuan Zhou, Context-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes, to appear in Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), New Orleans, USA, 2023
9. Dongsheng Wang, Miaoge Li, Xinyang Liu, MingSheng Xu, Bo Chen* and Hanwang Zhang, Tuning Multi-mode Token-level Prompt Alignment across Modalities, to appear in Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), New Orleans, USA, 2023
10. Zhibin Duan, Lv Zhiyi, Chaojie Wang, Bo Chen*, Bo An and Mingyuan Zhou, Few-shot Generation via Recalling the Episodic-Semantic Memory like Human Being, to appear in Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), New Orleans, USA, 2023
11. Ruiying Lu, YuJie Wu, Long Tian, Dongsheng Wang, Bo Chen, Xiyang Liu, Ruimin Hu, Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection, to appear in Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), New Orleans, USA, 2023.
12. Ruiying Lu, Bo Chen*, Dandan Guo, Dongsheng Wang, and Mingyuan Zhou, Hierarchical Topic-Aware Contextualized Transformers, to appear in IEEE Transactions on Audio, Speech, and Language Processing, 2023. 
13. Dongsheng Wang, Miaoge Li, Xinyang Liu, Zequn Zeng, Ruiying Lu, Bo Chen*, and Mingyuan Zhou, PatchCT: Aligning Patch Set and Label Set with Conditional Transport for Multi-Label Image Classification, International Conference on Computer Vision (ICCV), Paris, France, 2023.
14. Long Tian, Jingyi Feng, Wenchao Chen, Xiaoqiang Chai, Liming Wang, Xiyang Liu and Bo Chen, Prototypes-oriented Transductive Few-shot Learning with Conditional Transport, International Conference on Computer Vision (ICCV), Paris, France, 2023.
15. Yuxin Li, Wenchao Chen, Bo Chen*, Dongsheng Wang, Long Tian and Mingyuan Zhou, Prototype-oriented Unsupervised Anomaly Detection for Multivariate Time Series, International Conference on Machine Learning (ICML), Hawaii, 2023.
16. Zhibin Duan, Xinyang Liu, Yudi Su, Yi.shi Xu, Bo Chen* and Mingyuan Zhou, Bayesian Progressive Deep Topic Model with Knowledge Informed Textual Data Coarsening Process, International Conference on Machine Learning (ICML), Hawaii, 2023.
17. Zequn Zeng, Hao Zhang, zhengjue Wang, Ruiying Lu, Dongsheng Wang, Bo Chen*, ConZIC: Controllable Zero-shot Image Captioning by Sampling-Based Polishing, to appear in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
18. Dongsheng Wang, Yi.shi Xu, Miaoge Li, Zhibin Duan, Chaojie Wang, Bo Chen*, and Mingyuan Zhou, Knowledge-Aware Bayesian Deep Topic Model, to appear in Advances in Neural Information Processing Systems (NeurIPS, spotlight, top 5%), Virtual, 2022.
19. Yi.shi Xu, Dongsheng Wang, Bo Chen*, Ruiying Lu, Zhibin Duan, and Mingyuan Zhou, HyperMiner: Topic Taxonomy Mining with Hyperbolic Embedding, to appear in Advances in Neural Information Processing Systems (NeurIPS), Virtual, 2022.
20. Yewen Li, Chaojie Wang, Zhibin Duan, Dongsheng Wang, Bo Chen, Mingyuan Zhou, and Bo An, Alleviating "Posterior Collapse" in Deep Topic Models via Policy Gradient, to appear in Advances in Neural Information Processing Systems (NeurIPS), Virtual, 2022.
21. Yilin He, Chaojie Wang, Hao Zhang, Bo Chen, and Mingyuan Zhou, A Variational Edge Partition Model for Supervised Graph Representation Learning, to appear in Advances in Neural Information Processing Systems (NeurIPS), Virtual, 2022.
22. Chaojie Wang, Bo Chen*, Zhibin Duan, Wenchao Chen, Hao Zhang, and Mingyuan Zhou, Generative Text Convolutional Neural Network for Hierarchical Document Representation Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 45, no. 4, pp. 4586-4604, 1 April 2023,
23. Wenchao Chen, Long Tian, Bo Chen*, Liang Dai, Zhibin Duan and Mingyuan Zhou,Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection, to appear in International Conference on Machine Learning (ICML) 2022.
24. Zhibin Duan, Yishi Xu, Jianqiao Sun, Bo Chen*, Wenchao Chen, Chaojie Wang and Mingyuan Zhou, Bayesian Deep Embedding Topic Meta-Learner, to appear in International Conference on Machine Learning (ICML) 2022.
25. Ruiying Lu, Bo Chen*, Wenchao Chen, Penghui Wang, Hongwei Liu and Pramod K. Varshney, Heterogeneity-Aware Recurrent Neural Network for Hyperspectral and Multispectral Image Fusion,  to appear in IEEE Journal of Selected Topics in Signal Processing (IEEE J-STSP) 2022.
26. Dandan Guo, Ruiying Lu, Bo Chen*, Zequn Zeng and Mingyuan Zhou, Matching Visual Features to Hierarchical Semantic Topics for Image Paragraph Captioning, to appear in International Journal of Computer Vision, 2022.
27. Ziheng Cheng, Bo Chen*, Ruiying Lu, Zhengjue Wang, Hao Zhang, Ziyi Meng and Xin Yuan, Recurrent Neural Networks for Snapshot Compressive Imaging, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 45, no. 2, pp. 2264-2281, Feb. 2023.
28. Wenchao Chen, Bo Chen*, Yicheng Liu, Chaojie Wang, Xiaojun Peng, Hongwei Liu and Mingyuan Zhou, Infinite Switching Dynamic Probabilistic Network with Bayesian Nonparametric Learning, to appear in IEEE Transactions on Signal Processing 2022. 
29. Dongsheng wang, Dan dan Guo, He Zhao, Huangjie Zheng, Korawat Tanwisuth, Bo Chen* and Mingyuan Zhou*, Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings, to appear in International Conference on Learning Representations (ICLR), Virtual, April 2022.
30. Chang Gao, Junkun Yan, Xiaojun Peng, Bo Chen and Hongwei Liu, Intelligent multiframe detection aided by doppler information and a deep neural network, to appear in Information Sciences, 2022.
31. Hao Zhang, Long Tian, Zhengjue Wang, Yishi Xu, Pengyu Cheng, Ke Bai and Bo Chen, Multi-Scale Visual-Attribute Co-Attention for Zero-Shot Image Recognition, to appear in IEEE Transactions on Neural Networks and Learning Systems 2022.
32. Liang Dai,Wenchao Chen, Yanwei Liu, Antonios Argrious, Chang Liu, Penghui Wang, Zhen Xu, Bo Chen*, Switching Gaussian Mixture Variational RNN for Anomaly Detection of Diverse CDN Websites, to appear in IEEE INFOCOM, 2022.
33. Zhibin Duan, Yi.shi Xu, Bo Chen*, Dongsheng Wang, Chaojie Wang and Mingyuan Zhou, TopicNet: Semantic Graph-Guided Topic Discovery, to appear in Advances in Neural Information Processing Systems (NeurIPS), Virtual, 2021.
34. Korawat Tanwisuth, Xinjie Fan, Huangjie Zheng, Shujian Zhang, Hao Zhang, Bo Chen and Mingyuan Zhou, A Prototype-Oriented Framework for Unsupervised Domain Adaptation, to appear in Advances in Neural Information Processing Systems (NeurIPS), Virtual, 2021.
35. Ruiying Lu, Bo Chen*, Guanliang Liu, Ziheng Cheng, Mu Qiao and Xin Yuan*, Dual-view Snapshot Compressive Imaging via Optical Flow Aided Recurrent Neural Network, to appear in Internatiional Journal of Computer Vision (IJCV), 2021.
36. Yang Yang, Bo Chen*, and Hongwei Liu, Bayesian Compression for Dynamically Expandable Networks, to appear in Pattern Recognition, 2021.
37. Jian Wang, Yinghua Wang, Bo Chen, Hongwei Liu. LCS-EnsemNet: A semisupervised deep neural network for SAR image change detection with dual feature extraction and label-consistent self-ensemble[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14: 11903- 11925, 2021.
38. Dandan Guo, Bo Chen*, Meixi Zheng and Hongwei Liu, SAR Automatic Target Recognition based on Supervised Deep Variational Auto-encoding Model，to appear in IEEE Transactions on Aerospace and Electronic Systems, 2021.
39. Wenchao Chen, Bo Chen*, Yicheng Liu, Xiaojun Peng, Haoyang Fan, Fangxu Yu and Hongwei Liu, Bidirectional Recurrent Gamma Belief Network for HRRP Target Recognition, to appear in Signal Processing 2021.
40. Long Tian, Bo Chen*, Wenchao Chen, Yishi Xu and Hongwei Liu, Domain-aware Mmeta Nnetwork for Rradar HRRP Ttarget Rrecognition with Mmissing Aaspects, to appear in Signal Processing 2021., 
41. Zhibin Duan, Dongsheng Wang, Bo Chen*, Chaojie Wang, Wenchao Chen, Yewen Li, Jie Ren and Mingyuan Zhou, Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network, to appear in International Conference on Machine Learning (ICML) 2021.
42. Shujian Zhang, Xinjie Fan, Bo Chen and Mingyuan Zhou, Bayesian Attention Belief Networks, to appear in International Conference on Machine Learning (ICML) 2021.
43. Zhibin Duan, Hao Zhang, Chaojie Wang, Zhengjue Wang, Bo Chen*, and Mingyuan Zhou: EnsLM: Ensemble Language Model for Data Diversity by Semantic Clustering, to appear in the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) Bangkok, Thailand, 1-6 August 2021.
44. Chaojie Wang, Bo Chen*, Sucheng Xiao, Zhengjue Wang, Hao Zhang, Penghui Wang, Ning Han, and Mingyuan Zhou, Multimodal Weibull Variational Autoencoder for Jointly Modeling Image-Text Data, accepted by IEEE Transactions on Cybernetics, 2021. 
45. Wenchao Chen, Bo Chen*, Xiaojun Peng, Jiaqi Liu, Yang Yang, Hao Zhang and Hongwei Liu, Tensor RNN with Bayesian Nonparametric Mixture for Radar HRRP Modeling and Target Recognition，to appear in Transactions on Signal Processing, 2021.
46. Ziheng Cheng, Bo Chen*, Guanliang Liu, Hao Zhang, Ruiying Lu, Zhengjue Wang and X. Yuan*, Memory-Efficient Network for Large-scale Video Compressive Sensing, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
47. Zhengjue Wang, Hao Zhang, Ziheng Cheng, Bo Chen* and Xin Yuan*, MetaSCI: Scalable and Adaptive Reconstruction for Video Compressive Sensing, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
48. Wenchao Chen, Xuefei Cao, Bo Chen*, Yingqi Liu, Qianru Zhao, Hao Zhang, Max-Margin Deep Diverse Latent Dirichlet Allocation with continual learning, accepted by IEEE Transactions on Cybernetics, 2021.
49. Wenchao Chen, Chaojie Wang, Bo Chen*, Yicheng Liu, Hao Zhang and Mingyuan Zhou, Bidirectional Convolutional Poisson Gamma Dynamical Systems, to appear in Advances in Neural Information Processing Systems (NeurIPS), Virtual, 2020. [Code]
50. Chaojie Wang, Hao Zhang, Bo Chen*, Dongsheng Wang, Zhengjue Wang and Mingyuan Zhou, Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network, to appear in Advances in Neural Information Processing Systems (NeurIPS), Virtual, 2020. [Code]
51. Xinjie Fan, Shujian Zhang, Bo Chen and Mingyuan Zhou, Bayesian Attention Modules, to appear in Advances in Neural Information Processing Systems (NeurIPS), Virtual, 2020.
52. Dandan Guo, Bo Chen*, Wenchao Chen, Chaojie Wang, Hongwei Liu, and Mingyuan Zhou, Variational Temporal Deep Generative Model for Radar HRRP Target Recognition, to appear in IEEE Transactions on Signal Processing, 2020. 
53. Zhengjue Wang, Bo Chen*, Hao Zhang, and Hongwei Liu, Unsupervised Hyperspectral and Multispectral Images Fusion Based on Nonlinear Variational Probabilistic Generative Model, to appear in IEEE Transactions on Neural Networks and Learning Systems 2020.
54. Zhengjue Wang, Zhibin Duan, Hao Zhang, Chaojie Wang, Long Tian, Bo Chen* and Mingyuan Zhou, Friendly Topic Assistant for Transformer Based Abstractive Summarization, to appear in the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP2020, Dominican Republic, November, 2020. [Code]
55. Wei Wen, Bo Chen*, Xuefei Cao*, Xuefeng Zhang, Zhengjue Wang and Hongwei Liu, Infinite Bayesian Max-Margin Discriminant Projection, to appear in IEEE Transactions on Cybernetics 2020.
56. Ruiying Lu, Bo Chen*, Ziheng Cheng and Penghui Wang*, RAFnet: Recurrent Attention Fusion Network of Hyperspectral and Multispectral images, to appear in Signal Processing 2020.
57. Ziheng Cheng, Ruiying Lu, Zhengjue Wang, Hao Zhang, Bo Chen*, Ziyi Meng and Xin Yuan*, BIRNAT: Bidirectional Recurrent Neural Networks with Adversarial Training for Video Snapshot Compressive Imaging, to appear in European Conference on Computer Vision (ECCV), Glasgow, August 2020.  [Code]
58. Hao Zhang, Bo Chen*, Yulai Cong, Dandan Guo, Hongwei Liu, and Mingyuan Zhou，Deep Autoencoding Topic Model with Scalable Hybrid Bayesian Inference，to appear in IEEE Trans. on Pattern Analysis and Machine Intelligence. 
59. Zhengjue Wang, Bo Chen*, Ruiying Lu, Hao Zhang, Hongwei Liu, and Pramod K. Varshney, FusionNet: An Unsupervised Convolutional Variational Network for Hyperspectral and Multispectral Image Fusion, IEEE Trans. on Image Processing, Vol.29. 7565-7577, 2020.
60. Dandan Guo, Bo Chen*,  Ruiying Lu and Mingyuan Zhou, Recurrent Hierarchical Topic-Guided RNN for Language Generation, to appear in International Conference on Machine Learning (ICML), Vienna, Austria, July 2020. 

61. Wenchao Chen , Bo Chen*, Yicheng Liu, Qianru Zhao, Mingyuan Zhou, Switching Poisson Gamma Dynamical Systems, to appear in the 29th International Joint Conference on Artificial Intelligence (IJCAI), Yokohama, Japan, July, 2020.

62. Zhengjue Wang, Chaojie Wang, Hao Zhang, Zhibin Duan, Mingyuan Zhou, and Bo Chen*, Learning dynamic hierarchical topic graph with graph convolutional network for document classification, International Conference on Artificial Intelligence and Statistics (AISTATS2020), Palermo, Sicily, Italy, June 2020.

63. Hao Zhang, Bo Chen*, Long Tian, Zhengjue Wang and Mingyuan Zhou, Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling, in International Conference on Learning Representations (ICLR), Addis Ababa ETHIOPIA, May 2020. [Code]

64. Chaojie Wang, Bo Chen*, Sucheng Xiao, and Mingyuan Zhou, Convolutional Poisson Gamma Belief Network, to appear in International Conference on Machine Learning (ICML), Long Beach, CA, USA, June 2019. [Code]

65. Chang Gao, Junkun Yan, Shenghua Zhou, Bo Chen, and Hongwei Liu, Long Short-Term Memory-Based Recurrent Neural Networks for Nonlinear Target Tracking. Signal Processing, 164, 67-73, 2019.

66. Jinwei Wan, Bo Chen*, Bin Xu, Hongwei Liu and Lin Jin, Convolutional Neural Networks for Radar HRRP Target Recognition and Rejection, EURASIP, 2019(1):5, 2019.

67. Chuan Du, Bo Chen*, Hongwei Liu and Bin Xu, Factorized Discriminative Conditional Variational Auto-encoder for Radar HRRP Target Recognition, Signal Processing, 158, 176-189, 2019.

68. Zhengjue Wang, Bo Chen*, Hao Zhang and Hongwei Liu, Variational Probabilistic Generative Framework for Single Image Super-Resolution, Signal Processing, 156, 92-105, 2019.

69. Bin Xu, Bo Chen*, Jinwei Wan, Hongwei Liu, and Lin Jin, Target-Aware Recurrent Attentional Network for Radar HRRP Target Recognition, Signal Processing, 155, 268-280, 2019.

70. Dandan Guo, Bo Chen*, Hao Zhang, and Mingyuan Zhou, Deep Poisson Gamma Dynamic Systems, to appear in Advances in Neural Information Processing Systems (NIPS), 2018, Montreal, Canada.

71. Hao Zhang, Bo Chen*, Zhengjue Wang, and Hongwei Liu, Deep Max-Margin Discriminant Projection, IEEE Transactions on Cybernetics, Vol. 49, No. 7, 2454-2466, July 2019.

72. Hao Zhang, Bo Chen*, Dandan Guo, and Mingyuan Zhou, WHAI: Weibull hybrid autoencoding inference for deep topic modeling, to appear in International Conference on Learning Representations (ICLR), Vancouver, Canada, May 2018. [Code]
73. Chaojie Wang, Bo Chen*, Hongwei Liu, and Mingyuan Zhou, Multimodal Poisson Gamma Belief Network, to appear in the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), New Orleans, Lousiana, USA, Feburary 2018. [Code]
74. Yulai Cong, Bo Chen*, Hongwei Liu, and Mingyuan Zhou, Deep latent Dirichlet allocation with topic-layer-adaptive stochastic gradient Riemannian MCMC, to appear in International Conference on Machine Learning (ICML), Sydney, Australia, August 2017.
75. Yulai Cong, Bo Chen*, and Mingyuan Zhou, Fast simulation of hyperplane-truncated multivariate normal distributions, Bayesian Analysis, Vol. 12, No. 4, pp: 1017-1037, 2017. [Code]
76. Bo Feng, Bo Chen* and Hongwei Liu, Radar HRRP target recognition with deep networks, Pattern Recognition 61, 379-393, 2017.
77. Jing Chai, Bo Chen, Fan Liu, Zehua Chen, Xinghao Ding. Multiple-Instance Feature Extraction at the Bag and Instance Levels Using the Maximum-Trace Difference Criterion. Information Sciences: 2017 ,385-386 ,353-377.
78. Mingyuan Zhou*, Yulai Cong, and Bo Chen*, Augmentable gamma belief networks, Journal of Machine Learning Research,17(163), 1-44, 2016.

79. Yulai Cong, Bo Chen*, Hongwei Liu, Bo Jiu. Nonparametric Bayesian Attributed Scattering Center Extraction for Synthetic Aperture Radar Targets. IEEE Transactions on Signal Processing, 2016. Accepted for publication.

80. Jun Ding, Bo Chen*, Hongwei Liu, Mengyuan Huang, Convolutional Neural Network With Data Augmentation for SAR Target Recognition, IEEE Geoscience and Remote Sensing Letters, 13(3), 364-368, 2016.

81. Xuefeng Zhang, Bo Chen*, Hongwei Liu, Lei Zuo, and Bo Feng, Infinite max-margin factor analysis via data augmentation. Pattern Recognition 52, 17-32, 2016.

82. Hongwei Liu, Bo Feng, Bo Chen*, Lan Du, Radar high-resolution range profiles target recognition based on stable dictionary learning, IET Radar, Sonar & Navigation, Vol. 10, Iss. 2, pp. 228–237, 2016.

83. Mingyuan Zhou, Yulai Cong, Bo Chen, The Poisson Gamma Belief Network, Advances in Neural Information Processing Systems (NIPS). 3025-3033, 2015, Montreal, Canada.
84. Jun Liu, Weijian Liu, Bo Chen, Hongwei Liu, Hongbin Li, Chengpeng Hao, Modified Rao test for multichannel adaptive signal detection, IEEE Transactions on Signal Processing, 64(3), 714-725, 2015. 
85. Junkun Yan, Hongwei Liu, Bo Jiu, Bo Chen, Zheng Liu, Zheng Bao: Simultaneous Multibeam Resource Allocation Scheme for Multiple Target Tracking. IEEE Transactions on Signal Processing, 63(12): 3110-3122, 2015. (Impact Factor: 3.2)
86. Bo Chen, Hao Zhang, Xuefeng Zhang, Wei Wen, Hongwei Liu and Jun Liu, Max-Margin Discriminant Projection via Data Augmentation, IEEE Transactions on Knowledge and Data Engineering, 27(7), 1964-1976, 2015.(Impact Factor: 1.8)
87. Bo Jiu, Hongwei Liu, Xu Wang, Lei Zhang, Yinghua Wang, Bo Chen, Knowledge-Based Spatial-Temporal Hierarchical MIMO Radar Waveform Design Method for Target Detection in Heterogeneous Clutter Zone, IEEE Transactions on Signal Processing, 63(3), 543-554, 2015.(Impact Factor: 3.2)
88. Junkun Yan, Bo Jiu, Hongwei Liu, Bo Chen, Zheng Bao: Prior Knowledge-Based Simultaneous Multibeam Power Allocation Algorithm for Cognitive Multiple Targets Tracking in Clutter. IEEE Transactions on Signal Processing, 63(2): 512-527, 2015.(Impact Factor: 3.2)
89. Raymond J. Langley, Ephraim L. Tsalik, Jennifer C. van Velkinburgh, Seth W. Glickman, Brandon J. Rice, Chunping Wang, Bo Chen, Lawrence Carin, Arturo Suarez, Robert P. Mohney, Debra H. Freeman, Mu Wang, Jinsam You, Jacob Wulff, J. Will Thompson, M. Arthur Moseley, Stephanie Reisinger, Brian T. Edmonds, Brian Grinnell, David R. Nelson, Darrell L. Dinwiddie, Neil A. Miller, Carol J. Saunders, Sarah S. Soden, Angela J. Rogers, Lee Gazourian , Laura E. Fredenburgh, Anthony F. Massaro, Rebecca M. Baron, Augustine M.K. Choi, G. Ralph Corey, Geoffrey S. Ginsburg, Charles B. Cairns, Ronny M. Otero, Vance G. Fowler Jr, Emanuel P. Rivers, Christopher W. Woods, Stephen F. Kingsmore, An integrated clinico-me[ant]tabolomic model improves prediction of death in sepsis, Science Translational Medicine, Vol. 5, Issue 195, p. 195ra95, July, 2013. (Impact Factor: 10.8)
90. Bo Jiu, Hongwei Liu, Bo Chen, Zheng Liu, Waveform Design for Wideband Radar Target Recognition Based on Eigensubspace Projection, IET Radar, Sonar & Navigation,7(6), 702–709, 2013.(Impact Factor: 1.0)
91. Bo Chen, Gungor Polatkan, Guillermo Sapiro, David Blei, David Dunson and Lawrence Carin, Deep Learning with Hierarchical Convolutional Factor Analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(8), 1887-1901, 2013. (Impact Factor: 4.908)
92. Bo Chen, David E. Carlson and Lawrence Carin, On the Analysis of Multi-Channel Neural Spike Data, Neural Information Processing Systems (NIPS) 2011, Granada, Spain.
93. Bo Chen, Guillermo Sapiro, Gungor Polatkan, David Dunson and Lawrence Carin, The Hierarchical Beta Process for Convolutional Factor Analysis and Deep Learning, International Conference on Machine Learning, ICML 2011, Bellevue, Washington, USA. [online video: http://techtalks.tv/talks/54368/]
94. Bo Chen, Guillermo Sapiro, David Dunson, Lawrence Carin, Deep Networks with Hierarchical Convolutional Factor Analysis, Neural Information Processing Systems (NIPS) 2010 Workshop on Deep Learning and Unsupervised Feature Learning, Vancouver, Canada.
95. Bo Chen, Minhua Chen, John Paisley, Aimee Zaas, Christopher Woods, Geoff Ginsburg, Alfred Hero III, Joseph Lucas, David Dunson and Lawrence Carin. Bayesian inference of the number of factors in gene-ex[ant]pression analysis: application to human virus challenge studies. BMC Bioinformatics, Volume 11, Number 1, 552, 2010.(Impact Factor: 3.028)
96. Bo Chen, John Paisley and Lawrence Carin. Sparse Linear Regression with Beta Process Priors, ICASSP 2010, Dallas, USA.
97. Jing Chai, Hongwei Liu, Bo Chen and Zheng Bao. Large margin nearest local mean classifier. Signal Processing, Volume 90 Issue 1, January, 2010.(Impact Factor: 1.503)
98. Bo Chen, Hongwei Liu, Jing Chai and Zheng Bao. Large Margin Feature Weighting via Linear Programming. IEEE Transactions on Knowledge and Data Engineering, Vol 21, No 10,  1475-1488, 2009.(Impact Factor: 2.285)
99. Bo Chen, Hongwei Liu and Zheng Bao. Optimizing the Data-dependent Kernel under a Unified Kernel Optimization fr[ant]amework. Pattern Recognition, 41(6), 2107-2119, 2008. (Impact Factor: 3.172)
100. Bo Chen, Hongwei Liu and Zheng Bao. A Kernel Optimization Method Based on the Localized Kernel Fisher, Pattern Recognition, 41(3), 1098-1109, 2008. (Impact Factor: 3.172)
101. Bo Chen, Hongwei Liu, Li Yuan and Zheng Bao. Adaptively Segmenting Angular Sectors for Radar HRRP ATR. EURASIP Journal on Applied Signal Processing, Volume 2008 (2008), Article ID 641709, 6 pages. (Impact Factor: 1.055)
102. Bo Chen, Hongwei Liu and Zheng Bao. An Efficient Kernel Optimization Method for Radar High-resolution Range Profile Recognition, EURASIP Journal on Applied Signal Processing. Vol. 2007, Article ID 49597, 10 pages, 2007. (Impact Factor: 1.055)
103. Bo Chen, Li Yuan, Hongwei Liu and Zheng Bao. Kernel Subclass Discriminant Analysis. Neurocomputing, 71, 455-458, 2007.(Impact Factor: 1.595)
104. Bo Chen, Hongwei Liu and Zheng Bao. Basis Vector Classifier, Special issue of Dynamics of Continuous, Discrete and Impulsive Systems, 14 (s3), 23-29, 2007.
105. Bo Chen, Hongwei Liu, Zheng Bao. A Fusion Kernel Optimization Method. Journal of Xidian University, 34 (4), 509-513, 2007. (in Chinese)
106. Bo Chen, Hongwei Liu, Zheng Bao. Speeding up SVM in Test Phase: Application to Radar HRRP ATR. The Proc. of ICONIP’06, Hongkong, China, Vol.4232, 811-818, 2006, Springer Berlin.
107. Bo Chen, Hongwei Liu and Zheng Bao, An Efficient Kernel Optimization Method for High Range Resolution Profile Recognition, 2006 CIE International Conference on Radar, Shanghai, 1-4, 2006.
108. Bo Chen, Hongwei Liu and Zheng Bao, General Kernel Optimization Model Based on Kernel Fisher Criterion, ICNC2006, Xi’an, 143-146, Springer Berlin, 2006.
109. Bo Chen, Hongwei Liu, Zheng Bao. A Kernel Optimization Method Based on the Localized Kernel Fisher Criterion, ISNN2006, Chengdu, 915-921, Springer Berlin, 2006.
110. Bo Chen, Hongwei Liu, Zheng Bao. PCA and Kernel PCA for Radar High Range Resolution Profiles Recognition. 2005 IEEE International Radar Conference in Arlington, Virginia USA: pp.528-533.
111. Bo Chen, Hongwei Liu, Zheng Bao and Xuefei Cao. A Kernel Optimization Algorithm Based on Fusion Kernel for High Range Resolution Profiles Recognition. ACTA ELECTRONICA SINICA, 34 (6), 1146-1151, 2006. (in Chinese)
112. Bo Chen, Hongwei Liu and Zheng Bao. Analysis and Comparison of Three Kinds of Classification Based Different Absolute Alignment Methods. Modern Radar, Vol. 28 (3), 58-62, 2006. (in Chinese)
113. Bo Chen, Hongwei Liu and Zheng Bao. An HRRP Recognition Method Based on Zero Phase Representation. Journal of Xidian University, 32 (5), 657-662, 2005. (in Chinese)

 Patents:

1. Raymond Langley, Stephen Kingsmore, Bo Chen and Lawrence Carin, Method for diagnosis of sepsis and risk of death, Pub. Number: US 2010/0273207, Pub. date: 10.28, 2010.