G2Net - A network for Gravitational Waves, Geophysics and Machine Learning (CA17137)
ZOOM LINK FOR REMOTE PARTICIPANTS:
(please register your Name, Surname and email and you will receive a link to connect - the link will be valid for all days)
GITHUB REPOSITORY FOR TEACHING MATERIAL
In this github repository you will find all teaching material and notebooks, as well as the description of the hackathon (information will be added incrementally on a day-by-day basis, as the school progresses).
BUS LINES INFORMATION
Detailed information for public transportation can be found on this page.
AC sockets for laptop charging are available in the conference room (one per three seats). Please bring your own laptop and charger for the hands-on sessions.
WIFI ACCESS AT THE VENUE
Eduroam is available at the venue. In addition, in-person participants will also receive personal username/password combinations for the duration of the school.
The dinner will take place on Tuesday, March 28 at 20:00 at the Kazaviti restaurant in the Ladadika district (Katouni 9 Str.).
The G2Net COST action is organizing the 4th Training School on Gravitational Waves, Geophysics and Machine Learning in Thessaloniki, Greece. Our school will provide training in the exciting field of Gravitational Wave Astronomy, in which the application of machine learning (ML) techniques is rapidly evolving. The training modules are designed to provide students with a strong foundation in the fundamental concepts of machine learning techniques, as well as the practical skills and knowledge needed to apply these in the field of Gravitational Wave Astronomy, including the analysis of seismic noise. The school will be organized in a hybrid mode, with in-person attendance at the Aristotle University of Thessaloniki and remote attendance through live zoom sessions.
This training school is targeted towards PhD students and post-docs in Gravitational Wave Astronomy and Geophysics. Advanced MSc/BSc students are also welcome to apply.
- Machine Learning
- Deep Learning
- Gravitational Waves
- Seismic Noise
- Control Systems
Individual topics include rapid GW detection using neural networks, accelerating surrogate GW models with machine learning and denoising using machine learning. There will be hands-on exercise sessions using jupyter notebooks. Please bring your laptops.
The School will be organized in a hybrid mode, with in-person attendance (limited to about 40 persons) and remote attendance. Registration is required for both modes of participation. There are no registration fees. The final registration deadline is February 15, 2023.
Note: All participants accepted by the SOC, also need to register on the e-COST website and join the Working Group WG1 of COST Action CA17137 (G2Net), see these step-by-step instructions. You will then receive an official invitation from e-COST to attend the training school.
For in-person attendance, the G2Net action could support students who will attend the school in form of a travel grant, based on the availability of funds and a CV selection of candidates. To apply for a travel grant, please send your CV to the official email of the training school, with the subject "Travel grant application" by February 15 at the latest. You will be notified of acceptance shortly thereafter.
Scientific and Organizing Committee
Koloniari, Alexandra Eleni