Tim Z. Xiao

PhD student at University of Tübingen & International Max Planck Research School for Intelligent Systems


Hello! I am Tim, also known as Zhenzhong Xiao (肖镇中 in Chinese). Currently I am doing my PhD in machine learning at the University of Tübingen with Robert Bamler, and as a visiting PhD student at MPI-IS Tübingen with Weiyang Liu and Bernhard Schölkopf.

Previously, I did a MRes Computational Statistics and Machine Learning at UCL with David Barber and a MSc in Computer Science at the University of Oxford with Yarin Gal. Prior to that I studied computer science at the University of Manchester for my undergraduate. At the time, I also had an one year industrial placement with Morgan Stanley, during which I worked with a global team to create tools for managing and monitoring the cloud platform that has a huge number of servers located around the world.

Just like lots of computer scientists, I have faith in technology. Even though technology won’t solve all the problems for you, I believe it will certainly take you closer to the answers.

At the moment, I am very interested in Machine Learning, a field that has amazing impacts on human life.


Nov 3, 2023 I was invited to give a talk at Imperial College London - CSML reading group!
Nov 2, 2023 Check out our new workshop paper “The SVHN Dataset Is Deceptive for Probabilistic Generative Models Due to a Distribution Mismatch” to know more about distribution mismatch in the SVHN dataset!
Mar 13, 2023 Check out our new blog post “Large Language Models Are Zero-Shot Problem Solvers — Just Like Modern Computers” to find out the interesting connection between LLMs and modern computers!
Jan 20, 2023 Our paper “Trading Information between Latents in Hierarchical Variational Autoencoders” has been accepted at ICLR! :tada:
Jan 20, 2023 Our paper “Iterative Teaching by Data Hallucination” has been accepted at AISTATS! :tada:

selected publications

  1. vml_preview.png
    Verbalized Machine Learning: Revisiting Machine Learning with Language Models
    arXiv preprint arXiv:2406.04344, 2024
  2. unireps_rebasin.png
    A Compact Representation for Bayesian Neural Networks By Removing Permutation Symmetry
    Tim Z. XiaoWeiyang Liu, and Robert Bamler
    arXiv preprint arXiv:2401.00611, 2023
    NeurIPS 2023 Workshop on Unifying Representations in Neural Models
  3. svhn_remix.png
    The SVHN Dataset Is Deceptive for Probabilistic Generative Models Due to a Distribution Mismatch
    Tim Z. Xiao*Johannes Zenn*, and Robert Bamler
    arXiv preprint arXiv:2312.02168, 2023
    NeurIPS 2023 Workshop on Distribution Shifts
  4. 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
  5. uncertainty-transformer.png
    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