The Wednesday, March 15, 2017 Stats Seminar has been canceled due to inclement weather.
The Statistics Seminar speaker for Wednesday, March 15, 2017 will be Andrew Gordon Wilson, who joined the School of Operations Research and Information Engineering at Cornell University in August 2016 as an Assistant Professor. Previously, he was a research fellow in the machine learning department at CMU with Eric Xing and Alex Smola. He completed his PhD in machine learning with Zoubin Ghahramani at the University of Cambridge. Andrew specializes in kernel methods, deep learning, and probabilistic modelling.
Title: Scalable Gaussian Processes for Scientific Discovery
Abstract: More than ever before, we have access to massive datasets in almost every area of science and engineering. These datasets provide unprecedented opportunities to automatically discover rich statistical structure, from which we can derive new scientific discoveries.
Gaussian processes are rich distributions over functions, which can learn interpretable structure through covariance kernels. In this talk, I introduce a Gaussian process framework which is capable of learning expressive kernel functions on large datasets. I show how this framework can be extended to develop probabilistic deep learning models for characterizing uncertainty. I consider applications in epidemiology, change point modelling, counterfactuals, human learning, astronomy, inpainting. I will also present recent software packages implementing this work, and very recent results we have obtained for autonomous vehicles.