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Published year: 20204
Birds of a Feather Session on Machine Learning in Astronomy

Abstract

Not specified

Author: K. L. Polsterer

Date Published: 18th Nov 2020

Publication Type: InProceedings

Cataloguing the radio-sky with unsupervised machine learning: a new approach for the SKA era

Abstract

Not specified

Authors: T J Galvin, M T Huynh, R P Norris, X R Wang, E Hopkins, K Polsterer, N O Ralph, A N O’Brien, G H Heald

Date Published: 1st Sep 2020

Publication Type: Journal

Comparison of outlier detection methods on astronomical image data

Abstract (Expand)

Among the many challenges posed by the huge data volumes produced by the new generation of astronomical instruments there is also the search for rare and peculiar objects. Unsupervised outlier detection … algorithms may provide a viable solution. In this work we compare the performances of six methods: the Local Outlier Factor, Isolation Forest, k-means clustering, a measure of novelty, and both a normal and a convolutional autoencoder. These methods were applied to data extracted from SDSS stripe 82. After discussing the sensitivity of each method to its own set of hyperparameters, we combine the results from each method to rank the objects and produce a final list of outliers.

Authors: Lars Doorenbos, Stefano Cavuoti, Massimo Brescia, Antonio D'Isanto, Giuseppe Longo

Date Published: 2020

Publication Type: Journal

Integration of Distributed Parallel Simulation Environment with Cloud-Infrastructures

Abstract (Expand)

This article describes an integration of the subsystems of the distributed parallel simulation environment with cloud infrastructures. A complex support for simulation of the dynamic network object … with distributed parameters on Amazon AWS cloud is provided. As well as a tool helping to significantly save running costs for cloud simulations.

Authors: O. Shcherbakov, Kai L. Polsterer, V. A. Svyatnyy

Date Published: 2020

Publication Type: InProceedings

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