Refereed Journal and Conference Papers

2022

  1. Lirong He, Qingzhong Ai, Yuqing Lei, Lili Pan, Yazhou Ren, and Zenglin Xu, Edge Enhancement Improves Adversarial Robustness in Image Classification. Neurocomputing (Neurocomputing) (IF = 5.779, JCR Q1, 中科院 Q2)

2021

  1. Liangjian Wen, Haoli Bai, Lirong He, Yiji Zhou, Mingyuan Zhou, and Zenglin Xu, Gradient Estimation of Information Measures in Deep Learning. Knowledge-Based Systems (KBS). vol. 224, 2021: 107046 (IF = 8.083 in 2020, JCR Q1, 中科院 Q1)
  2. Qingzhong Ai, Lirong He, Shiyu Liu, and Zenglin Xu, ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE. The 35th Conference on Neural Information Processing Systems (NeurIPS-2021). Virtual-only Conference, December 6th - 14th, 2021 (CCF-A)

2020

  1. Liangjian Wen, Yiji Zhou, Lirong He, Mingyuan Zhou, and Zenglin Xu, Mutual Information Gradient Estimation for Representation Learning. The 8th International Conference on Learning Representations (ICLR-2020). Addis Ababa, Ethiopia, April 26 - May 1 2020

2019

  1. Lirong He, Ziyi Guo, Kaizhu Huang, and Zenglin Xu, Deep Minimax Probability Machine. The 19th IEEE International Conference on Data Mining (ICDM-2019 Workshop). Beijing, China, November 8-11 2019

2018

  1. Hao Liu, Lirong He, Haoli Bai, Kun Bai, and Zenglin Xu, Structured Inference for Recurrent Hidden Semi-markov Model. The 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI-2018). Stockholm, Sweden, July 13 - 19 2018 (CCF: A)
  2. Lirong He, Bin Liu, Guangxi Li, Yongpan Sheng, Yafang Wang, and Zenglin Xu, Knowledge Base Completion by Variational Bayesian Neural Tensor Decomposition. Cognitive Computation (Cognitive Computation). accepted (IF = 3.479, JCR Q1, 中科院 Q2)
  3. Bin Liu, Lirong He, Yingming Li, Shandian Zhe, and Zenglin Xu, NeuralCP: Bayesian Multiway Data Analysis with Neural Tensor Decomposition. Cognitive Computation (Cognitive Computation). accepted (IF = 3.479, JCR Q1, 中科院 Q2)

Before 2018

  1. Hao Liu, Lirong He, Haoli Bai, and Zenglin Xu, Efficient Structured Inference for Stochastic Recurrent Neural Networks. The 34th International Conference on Machine Learning (ICML-2017 Workshop). Sydney, Australia, August 6 - 11 2017
  2. Liqiang Wang, Yafang Wang, Bin Liu, Lirong He, Shijun Liu, Gerard de Melo, and Zenglin Xu, Link prediction by exploiting network formation games in exchangeable graphs. The 2017 International Joint Conference on Neural Networks (IJCNN-2017). Anchorage, United States, May 14 - 19 2017 (CCF-C)
  3. Zenglin Xu, Yongpan Sheng, Lirong He, and Yafang Wang, Review on Knowledge Graph Techniques. Journal of University of Electronic Science and Technology of China (JUESTC). vol. 24, no. 4 (2016): 589-606. (In Chinese)