My areas of interest in machine learning include Bayesian deep learning, deep probabilitic models and their applications.


  1. hit_3d.png
    Trading Information between Latents in Hierarchical Variational Autoencoders
    Tim Z. Xiao, and Robert Bamler
    In International Conference on Learning Representations (ICLR), 2023
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    Iterative Teaching by Data Hallucination
    Zeju Qiu, Weiyang LiuTim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, and 1 more author
    In International Conference on Artificial Intelligence and Statistics (AISTATS), 2023


  1. Out-of-Distribution Detection with Class Ratio Estimation
    Mingtian ZhangAndi ZhangTim Z. Xiao, Yitong Sun, and Steven McDonagh
    arXiv preprint arXiv:2206.03955, 2022
    NeurIPS 2022 Workshop on Machine Learning Safety
  2. Improving VAE-Based Representation Learning
    Mingtian ZhangTim Z. Xiao, Brooks Paige, and David Barber
    arXiv preprint arXiv:2205.14539, 2022


  1. Locally-Contextual Nonlinear CRFs for Sequence Labeling
    Harshil Shah, Tim Z. Xiao, and David Barber
    arXiv preprint arXiv:2103.16210, 2021
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    Exploiting Semi-Supervised Generative Model in Active Learning
    Tim Z. Xiao
    University College London, 2021
    Master’s Thesis at UCL


  1. uncertainty-qa.png
    You Need Only Uncertain Answers: Data Efficient Multilingual Question Answering
    Zhihao Lyu, Danier Duolikun, Bowei Dai, Yuan Yao, Pasquale Minervini, Tim Z. Xiao, and Yarin Gal
    ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning, 2020
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    Wat zei je? Detecting Out-of-Distribution Translations with Variational Transformers
    Tim Z. XiaoAidan N. Gomez, and Yarin Gal
    arXiv preprint arXiv:2006.08344, 2020
    Spotlight talkNeurIPS 2019 Workshop on Bayesian Deep Learning


  1. A partial reconfiguration controller for Altera Stratix V FPGAs
    Zhenzhong Xiao, Dirk Koch, and Mikel Lujan
    In International Conference on Field Programmable Logic and Applications (FPL), 2016