Yee Whye Teh
Yee Whye Teh | |
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| Alma mater | University of Waterloo B.Math. (1997) University of Toronto Ph.D. (2003) |
| Known for | Hierarchical Dirichlet process deep belief network |
| Scientific career | |
| Fields | Machine Learning |
| Institutions | University of Oxford DeepMind |
| Doctoral advisor | Geoffrey Hinton (Toronto) |
| Website | www |
Yee Whye Teh is a Professor of Statistical Machine Learning in the Department of Statistics at the University of Oxford. Prior to 2012 he was a reader at the Gatsby Computational Neuroscience Unit at University College London. His work is primarily in machine learning.
Research[]
He was one of the original developers of deep belief networks and of hierarchical Dirichlet processes.
External links[]
Honors[]
He was a keynote lecturer at UAI 2019, and was invited to give the Breiman lecture at NeurIPS 2017 (formally known as NIPS), on the topic Bayesian Deep Learning and Deep Bayesian Learning. He was program co-chair of ICML 2017, one of the premier conferences in machine learning.
Authority control: Scientific databases  |
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Categories:
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- Artificial intelligence researchers
- Machine learning researchers
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