Research Interest

My research interest mainly covers machine learning, especially deep learning & bayesian learning, with application in Natural Language Processing (NLP). Specific topics I have been working on include:

  • Deep generative models such as VAE and GAN; text generation
  • Large-scale Bayesian sampling and variational inference

I am open to interesting research topics and engineering problems in applied machine learning field.

Conference Papers

  1. Le Fang, Chunyuan Li, Jianfeng Gao, Wen Dong, and Changyou Chen. "Implicit Deep Latent Variable Models for Text Generation", in Conference on Empirical Methods in Natural Language Processing (EMNLP) 2019. [arxiv] [Blog] [Poster] [Github]
  2. Yifang Liu, Seyed Mahdi Shamsi, Le Fang, Changyou Chen, Nils Napp. "Deep Q-Learning for Dry Stacking Irregular Objects", in International Conference on Intelligent Robots (IROS) 2018
  3. Le Fang, Fan Yang, Wen Dong, Tong Guan, and Chunming Qiao. "Expectation Propagation with Stochastic Kinetic Model in Complex Interaction Systems", in Conference on Neural Information Processing Systems (NIPS) 2017
  4. Tong Guan, Le Fang, Wen Dong, Yunfei Hou, and Chunming Qiao. "Indoor localization with asymmetric grid-based filters in large areas utilizing smartphones", in IEEE International Conference on Communications (ICC) 2017
  5. Tong Guan, Le Fang, Wen Dong, and Chunming Qiao. "Robust indoor localization with smartphones through statistical filtering", in International Conference on Computing, Networking and Communications (ICNC) 2017
  6. Le Fang, Tong Guan, Wen Dong, Chunming Qiao, "Event-Based Social Network Discovery (ESONED) Using WiFi Access Points", in International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction (SBP-BRiMS) 2016

Journal Papers

  1. Tong Guan, Le Fang, Wen Dong, Dimitrios Koutsonikolas, Geoffrey Challen and Chunming Qiao. "Robust, cost-effective and scalable localization in large indoor areas". Computer Networks, 2017