Graduate Student Statistics Seminar Speaker: Andrew Gordon Wilson, 4/11/17

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Tuesday Apr 11 2017

Graduate Student Statistics Seminar Speaker: Andrew Gordon Wilson, 4/11/17

4:45pm @ Malott 203

The Graduate Student Seminar Speaker for Tuesday, April 11, 2017 will be Andrew Gordon Wilson. 

Title: Deep Learning with Uncertainty

Abstract: In this talk, we approach model construction from a probabilistic perspective. First, we introduce a scalable Gaussian process framework capable of learning expressive kernel functions on large datasets. We then develop this framework into an approach for deep kernel learning, with non-parametric capacity, inductive biases given by deep architectures, full predictive distributions, and automatic complexity calibration. We will consider applications in image inpainting, crime prediction, epidemiology, counterfactuals, autonomous vehicles, astronomy, and human learning, including very recent state of the art results.

Bio: Andrew Gordon Wilson joined ORIE 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.