Stefan Webb

Stefan Webb

deep learning, deep generative models, probabilistic inference, neural network verification

I am a final year DPhil student in the AIMS centre for doctoral training at Oxford supervised by Prof. M. Pawan Kumar and Prof. Yee Whye Teh. I am interested in advancing the state-of-the-art in Deep Generative Models, and developing new architectures and applications for them. During my DPhil, I’ve worked on distributed Bayesian learning, improving the design of inference networks, an importance component of amortized inference, as well as developing a new framework for neural network verification (under review).

Publications

2018

  • S. Webb , A. Golinski , R. Zinkov , N. Siddharth , T. Rainforth , Y. W. Teh , F. Wood , Faithful Inversion of Generative Models for Effective Amortized Inference, in Advances in Neural Information Processing Systems (NIPS), 2018.

2017

  • L. Hasenclever , S. Webb , T. Lienart , S. Vollmer , B. Lakshminarayanan , C. Blundell , Y. W. Teh , Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server, Journal of Machine Learning Research, vol. 18, no. 106, 1–37, 2017.
    Project: sgmcmc

2015

  • L. Hasenclever , S. Webb , T. Lienart , S. Vollmer , B. Lakshminarayanan , C. Blundell , Y. W. Teh , Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server, 2015.
    Project: sgmcmc

Software

2016

  • L. Hasenclever , S. Webb , T. Lienart , S. Vollmer , B. Lakshminarayanan , C. Blundell , Y. W. Teh , Posterior Server. 2016.
    Project: sgmcmc