Projects

Dimensionality Reduction

Dimensionality reduction is a topic that permeates many of our interests. An important application for dimensionality reduction is visualisation: “compressing” data to two dimensions allows us a visual appreciation of the dataset at hand possibly revealing relationships of data similarity. This compression of data is often done in ad hoc way that disregards the particular nature of…

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Redshift Estimation

We developed a new method to statistically estimate the redshift z based on a similarity approach. This allows to determine spectral redshifts in emission as well as in absorption independently without using any predefined model. The redshift estimation is performed by comparing predefined regions in the spectra and applying a k-nearest neighbor regression model for emission and…

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Galaxy morphology

In the last decades more and more all-sky-surveys created an enormous amount of data which is publicly available on the internet. Crowd-sourcing projects like Galaxy-Zoo or Radio-Galaxy-Zoo used encouraged users from all over the world to manually conduct various classification tasks. The combination of the pattern-recognition capabilities of thousands of volunteers enabled scientists to do…

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Time series analysis

The project aims to develop methods that can handle time series in unsupervised and supervised scenarios. Time series are often treated as vectorial data by data analysts and scientists. Such a view discards the potentially interesting and latent dynamics that a time series might possess. Our aim is to explicitly capture these important characteristics and…

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