Christian Szegedy is a Research Scientist at Google. His research machine learning methods such as the inception architecture, batch normalization and adversarial examples, and he currently investigates machine learning for mathematical reasoning.
Christian’s PhD thesis is titled "Some Applications of the Weighted Combinatorial Laplacian" which he completed in 2005 at the University of Bonn. We discuss Christian’s background in mathematics, his PhD work on areas of both pure and applied mathematics, and his path into machine learning research. Finally, we discuss his recent work with using deep learning for mathematical reasoning and automatically formalizing mathematics.
Episode notes: https://cs.nyu.edu/~welleck/episode15.html
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