Yee Whye Teh
Statistical Machine Learning
Department of Statistics, University of Oxford
I am a professor at the Department of Statistics of the University of Oxford and a research scientist at DeepMind. I work on statistical machine learning, with particular focus on probabilistic learning, deep learning, meta learning, Bayesian nonparametrics, variational inference, and Monte Carlo.
Please see here for information for prospective students. I am unfortunately not able to respond to emails or requests to meet regarding graduate admissions, due to the large volumn of such requests. If you are interested in doing research with me just apply to the appropriate graduate programmes directly. I am also not able to take on internship students this year.
My email stack is very deep, and emails often fall off it and disappear into the ether. If you have emailed me and have not received any replies within a month, please resend, I would appreciate the reminder.
I am teaching Advanced Topics in Statistical Machine Learning this term. Course details.
Along with Chris Holmes and Sami Kaski, I am co-directing an ELLIS programme on Robust Machine learning.
I enjoyed giving a keynote lecture at UAI 2019. Slides are here.
I am also very fortunate to be able to give an IMS Medallion lecture at JSM 2019. Slides are here.
I gave the Breiman Lecture on Bayesian Deep Learning and Deep Bayesian Learinng at NIPS 2017.
Along with Doina Precup, I was programme co-chair for ICML 2017.
The machine learning, computational statistics, and statistical methods group has a new website! I have an up-to-date publications and software list there.