Patrick Schnider: Catalogue data in Spring Semester 2023 |
| Name | Dr. Patrick Schnider |
| Address | Gärtner, Bernd (Tit.-Prof.) ETH Zürich, OAT Z 13.1 Andreasstrasse 5 8092 Zürich SWITZERLAND |
| patrick.schnider@inf.ethz.ch | |
| URL | http://people.inf.ethz.ch/schnpatr/ |
| Department | Computer Science |
| Relationship | Lecturer |
| Number | Title | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||
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| 263-4203-00L | Geometry: Combinatorics and Algorithms  The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | 2 credits | 2S | B. Gärtner, M. Hoffmann, E. Welzl, P. Schnider | |||||||||||||||||||||||||||||
| Abstract | This seminar complements the course Geometry: Combinatorics & Algorithms. Students of the seminar will present original research papers, some classic and some of them very recent. | ||||||||||||||||||||||||||||||||
| Learning objective | Each student is expected to read, understand, and elaborate on a selected research paper. To this end, (s)he should give a 45-min. presentation about the paper. The process includes * getting an overview of the related literature; * understanding and working out the background/motivation: why and where are the questions addressed relevant? * understanding the contents of the paper in all details; * selecting parts suitable for the presentation; * presenting the selected parts in such a way that an audience with some basic background in geometry and graph theory can easily understand and appreciate it. | ||||||||||||||||||||||||||||||||
| Content | This seminar is held once a year and complements the course Geometry: Combinatorics & Algorithms. Students of the seminar will present original research papers, some classic and some of them very recent. The seminar is a good preparation for a master, diploma, or semester thesis in the area. | ||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Prerequisite: Successful participation in the course "Geometry: Combinatorics & Algorithms" (takes place every HS) is required. | ||||||||||||||||||||||||||||||||
| 263-4510-00L | Introduction to Topological Data Analysis | 8 credits | 3V + 2U + 2A | P. Schnider | |||||||||||||||||||||||||||||
| Abstract | Topological Data Analysis (TDA) is a relatively new subfield of computer sciences, which uses techniques from algebraic topology and computational geometry and topology to analyze and quantify the shape of data. This course will introduce the theoretical foundations of TDA. | ||||||||||||||||||||||||||||||||
| Learning objective | The goal is to make students familiar with the fundamental concepts, techniques and results in TDA. At the end of the course, students should be able to read and understand current research papers and have the necessary background knowledge to apply methods from TDA to other projects. | ||||||||||||||||||||||||||||||||
| Content | Mathematical background (Topology, Simplicial complexes, Homology), Persistent Homology, Complexes on point clouds (Čech complexes, Vietoris-Rips complexes, Delaunay complexes, Witness complexes), the TDA pipeline, Reeb Graphs, Mapper | ||||||||||||||||||||||||||||||||
| Literature | Main reference: Tamal K. Dey, Yusu Wang: Computational Topology for Data Analysis, 2021 https://www.cs.purdue.edu/homes/tamaldey/book/CTDAbook/CTDAbook.html Other references: Herbert Edelsbrunner, John Harer: Computational Topology: An Introduction, American Mathematical Society, 2010 https://bookstore.ams.org/mbk-69 Gunnar Carlsson, Mikael Vejdemo-Johansson: Topological Data Analysis with Applications, Cambridge University Press, 2021 https://www.cambridge.org/core/books/topological-data-analysis-with-applications/00B93B496EBB97FB6E7A9CA0176F0E12 Robert Ghrist: Elementary Applied Topology, 2014 https://www2.math.upenn.edu/~ghrist/notes.html Allen Hatcher: Algebraic Topology, Cambridge University Press, 2002 https://pi.math.cornell.edu/~hatcher/AT/ATpage.html | ||||||||||||||||||||||||||||||||
| Prerequisites / Notice | The course assumes knowledge of discrete mathematics, algorithms and data structures and linear algebra, as supplied in the first semesters of Bachelor Studies at ETH. | ||||||||||||||||||||||||||||||||
| Competencies |
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