Dear all,
You are all invited to this week's NOMADS seminar at GSSI. The seminar will be given by Martin Stoll from TU-Chemnitz (Germany). Title, abstract and zoom link are below. Further info about past and future meetings are available at the webpage: https://num-gssi.github.io/seminar/
Please feel free to distribute this announcement as you see fit.
Hope to see you all on Wednesday! Francesco and Nicola
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Title: From PDEs to data science: an adventure with the graph Laplacian
Abstract: In this talk we briefly review some basic PDE models that are used to model phase separation in materials science. They have since become important tools in image processing and over the last years semi-supervised learning strategies could be implemented with these PDEs at the core. The main ingredient is the graph Laplacian that stems from a graph representation of the data. This matrix is large and typically dense. We illustrate some of its crucial features and show how to efficiently work with the graph Laplacian. In particular, we need some of its eigenvectors and for this the Lanczos process needs to be implemented efficiently. Here, we suggest the use of the NFFT method for evaluating the matrix vector products without even fully constructing the matrix. We illustrate the performance on several examples.
Zoom: https://us02web.zoom.us/j/81317396646
— Francesco Tudisco Assistant Professor School of Mathematics GSSI Gran Sasso Science Institute Web: https://ftudisco.gitlab.io
Dear all, I am so sorry for the multiple messages. I forgot to include date and time of the seminar in my previous email: Martin Stoll, Wednesday December 2, 17:00
All the best, Francesco
On 30/11/2020 9:20 am, Francesco Tudisco wrote:
Dear all,
You are all invited to this week's NOMADS seminar at GSSI. The seminar will be given by Martin Stoll from TU-Chemnitz (Germany). Title, abstract and zoom link are below. Further info about past and future meetings are available at the webpage: https://num-gssi.github.io/seminar/
Please feel free to distribute this announcement as you see fit.
Hope to see you all on Wednesday! Francesco and Nicola
==================================================
Title: From PDEs to data science: an adventure with the graph Laplacian
Abstract: In this talk we briefly review some basic PDE models that are used to model phase separation in materials science. They have since become important tools in image processing and over the last years semi-supervised learning strategies could be implemented with these PDEs at the core. The main ingredient is the graph Laplacian that stems from a graph representation of the data. This matrix is large and typically dense. We illustrate some of its crucial features and show how to efficiently work with the graph Laplacian. In particular, we need some of its eigenvectors and for this the Lanczos process needs to be implemented efficiently. Here, we suggest the use of the NFFT method for evaluating the matrix vector products without even fully constructing the matrix. We illustrate the performance on several examples.
Zoom: https://us02web.zoom.us/j/81317396646
— Francesco Tudisco Assistant Professor School of Mathematics GSSI Gran Sasso Science Institute Web: https://ftudisco.gitlab.io
— Francesco Tudisco Assistant Professor School of Mathematics GSSI Gran Sasso Science Institute Web: https://ftudisco.gitlab.io
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Francesco Tudisco