A central activity at the workshop will be the half-day "hackathons" where attendees can collaborate hands-on on applying deep learning methods in their physics analysis, developing new reconstruction techniques, integrating their experiment or similar — all using the GraphNeT framework.
We encourage participants to bring problems, and possibly data, that they would like to work on during the hackathons using GraphNeT.
- getting GraphNeT installed and training your first model. The organisers will prepare some standard, experiment-independent data based on the recent IceCube Kaggle challenge. This will allow anyone to get up and running quickly.
- applying GraphNeT to data from your own experiment (that is not IceCube). In this case you should, in advance, consider which data could be used to test this out, and ideally bring it along for the hackathon.
- Implementing a deep learning method from your experiment into GraphNeT
The GraphNeT developers will be around to help you get setup, running, and and extending the framework.
On Thursday morning, teams are encouraged to present their hackathon results.
