Machine Learning Tools for Research in Astronomy
Harnessing the tools of Machine Learning methods for analysis and discovery in observations and simulations
Annalisa Pillepich (MPIA)
Gianfranco Bertone (U. of Amsterdam)
David W Hogg (NYU, Flatiron Inst.)
Kai Polsterer (HITS)
Michelle Ntampaka (Harvard)
Glenn van de Ven (U. of Vienna)
Machine learning methods can reveal the relations between observational data and the properties of the observed objects. They simultaneously have the potential to complement and inform the build up of physical models, provide data-driven predictions for practical applications, and automatize the analysis and comparisons of large data sets (real or simulated).
A number of machine learning tools have already been proven successful in a variety of astrophysical contexts, e.g. from the measurement of galaxy morphologies to automatic object detection and identification (e.g. quasars in the early Universe or RR Lyrae stars around the Milky Way), streamlined estimation of galaxies’ redshifts, and image analysis techniques for de-noising and deconvolution. In the upcoming years efficient machine learning and image analysis algorithms will become of the essences to fully exploit the available data and make substantial progress in our understanding of astrophysical phenomena.
We are therefore planning a hands-on and interactive workshop to foster big-data and machine-learning proficiency in the astronomy community, with particular focus on applications, among others, pertaining extra-galactic and galactic astronomy, galaxy formation, large scale structure, cosmology and cosmological surveys. Tools will range from classical regression and classification methods to state-of-the-art deep learning algorithms as generative adversarial networks and variational autoencoders. We plan to invite to participate also a few representatives of big and small private companies, in order to favor the percolation of their know-how expertise to the astronomy community.
The workshop will be held in the Schloss Ringberg, overlooking the Tegernsee Lake, in Southern Bavaria. Lodging and meals will be provided at the castle as well. For more information on the castle see here.
All participants will be lodged at the Castle for the duration of the program.
Breakfast, Lunch, and Dinner will all be provided at the Castle as well. The first meal will be a light dinner on Sunday evening. The last meal served will be Lunch on Friday, just before departure. Vegetarian options will be possible as well.
Please make sure to check that your passport is up-to-date before finalizing your travel arrangements!
Depending on where you live, you may or may
not need to apply for a visa to enter
For information by country, please see this overview of visa requirements.
If you are arriving by plane we recommend that you fly into Munich Airport (MUC), as this is the nearest international airport to Schloss Rinberg. Arrivals by train should be made to the Munich main train station.
It is possible to travel by train from Munich Airport to the Tegernsee Station (via Munich Main Station) in about 2 hours for about 23 EUR. From the Munich Main Station The trip takes about 1 hour and costs about 15 EUR. See www.bahn.de for schedule and tickets.
From the Tegernsee train station the best way to get to the castle is to take a taxi cab: there are not many trains arriving into Tegernsee, so look around for other conference people to share the taxi ride. There are usually a few taxi cabs at the station otherwise please contact Taxi Kaufmann (www.taxi-kaufmann.de) Tel. +49 (0)8022 / 5555.
The road up to the castle during the winter is very steep and is likely to be covered in snow. It is strongly recommended not to attempt it without a proper vehicle (4x4), tires, and experience.
Instructions on how to arrive at the castle can also be found here.
If you choose to use a different airport and would like assistance organizing travel to the conference please contact the LOC.
The SOC and LOC are committed to creating an environment that is safe, professional and of mutual trust where diversity and inclusion are valued, and where everyone is entitled to be treated with courtesy and respect. As conference organisers we are committed to making this workshop, and all associated activities productive and enjoyable for everyone. We will not tolerate harassment of participants in any form.
Please follow these guidelines:
The designated contact points for any issue relating to this Code of Conduct, from the SOC and LOC are Annalisa Pillepich and Elad Zinger. Participants can report any violation of these guidelines to these designates in confidence. If asked to stop inappropriate behaviour participants are expected to comply immediately and, in serious cases, may be asked to leave the event. The organizers will not tolerate retaliation against anyone reporting violations of this code of conduct.
Acknowledgement: This code of conduct is based on the ESO Code of Conduct for Workshops & Conferences.