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Hi, I’m Hung, a fourth year Math major at the University of Chicago. I’m currently interested in the theory of deep learning! My thoughts are recently inspired by, in no order:

• Misha Belkin’s blog posts on the necessity of developing a deep learning theory.
• Rebecca Willett’s motivation for her research directions.
• The book The Principles of Deep Learning Theory.

Besides all this, I am also interested in reinforcement learning and its theoretical foundations. Because I love robots. There are not as many “inspirations” here as there are above, but I do think a lot of future success in RL hinges on the simpler DL case.

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Current curiosities: unsupervised RL, mode connectivity, plasticity, physics for deep learning theory