Seminar: Large Deviations (SoSe20)

The seminal result in probability is the central limit theorem, a tool that tells us how ever larger sums of random variables fluctuate around their mean. A natural question that one might pose at this stage is: how can we describe events where this sum deviates from its mean by more than a “normal’’ amount? Answering this questions plays a crucial role in many fields such as probability theory, statistics, financial mathematics, operations research, ergodic theory, information theory, statistical physics and many more. In this seminar we will look at large deviation theory, by first looking at a toy example of sums of i.i.d. random variables. Once the basic concepts are understood, we will present the result in a more abstract/general way and look at a few more tailored statements.

  • Frank den Hollander. Large Deviations. American Mathematical Soc., 2008.
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Course: Probability Theory II (WS19/20)
(Wahrscheinlichkeitstheorie II)


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Since this is supposed to be a sort of CV website, I should probably list a couple of things that define me. In no specific order, here's a few things I have done.