Author Archives: Fabrice Baudoin

Lecture 5. Rough paths. Fall 2017

In this lecture we define the Young‘s integral when and with . The cornerstone is the following Young-Loeve estimate. Theorem: Let and . Consider now with . The following estimate holds: for , Proof: For , let us define We … Continue reading

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MA3160. HW2. Due 09/16/2021

Exercise 1. Suppose that A and B are pairwise disjoint events for which P(A) = 0.3 and P(B) = 0.5.   What is the probability that B occurs but A does not?   What is the probability that neither A nor … Continue reading

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Lecture 4. Rough paths. Fall 2017

Our next goal in this course is to define an integral that can be used to integrate rougher paths than bounded variation. As we are going to see, Young’s integration theory allows to define as soon as has finite -variation … Continue reading

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Lecture 3 Rough paths. Fall 2017

Let and let be a Lipschitz continuous map. In order to analyse the solution of the differential equation, and make the geometry enter into the scene, it is convenient to see as a collection of vector fields , where the … Continue reading

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Rough paths theory Fall 2017. Lecture 2

In this lecture we establish the basic existence and uniqueness results concerning differential equations driven by bounded variation paths and prove the continuity in the 1-variation topology of the solution of an equation with respect to the driving signal. Theorem: … Continue reading

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HW1. MA3160. Due 09/09/2021

Suppose a License plate must consist of a combination of 8 numbers or letters. How many license plates are there if: there can only be letters?  the first three places are numbers and the last five are letters? the first … Continue reading

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Rough paths theory Fall 2017. Lecture 1

The first few lectures are essentially reminders of undergraduate real analysis materials. We will cover some aspects of the theory of differential equations driven by continuous paths with bounded variation. The point is to fix some notations that will be … Continue reading

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MA3160 Probability. Syllabus

The main educational resource for MA3160 is the following webpage: UConn Undergraduate Probability OER. No book is required and the course will mostly be based on the lecture notes posted here. There will be two midterm exams and a final exam … Continue reading

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Rough paths theory. Fall 2017

During the Fall 2017, I will be teaching rough paths theory at the University of Connecticut. The course will be mainly based on those   notes and the lectures already posted on this blog in 2013 (when I first taught the class … Continue reading

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MA5311. Take home exam

Exercise 1. Solve Exercise 44 in Chapter 1 of the book. Exercise 2.  Solve Exercise 3 in Chapter 1 of the book. Exercise 3.  Solve Exercise 39 in Chapter 1 of the book. Exercise 4. The heat kernel on is given by . By … Continue reading

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