About
Surrogate generative models demonstrate extraordinary progress in current years. Although most applications are dedicated to image generation and similar commercial goals, this approach is also very promising for natural sciences, especially for tasks like fast event simulation in HEP experiments. However, application of such generative models to scientific research implies specific requirements and expectations from these models. In the presentation, I'll discuss specific points which need attention when using generative models for scientific research. This includes ensuring that models satisfy different boundary conditions and match scientifically important but marginal statistics. We also need to establish procedures to evaluate the quality of the particular model, propagate model imperfection into systematic uncertainties of the final scientific result, and so on..
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The talk
Credits and licence
- Institution
- CERN
- Department
- LPCC Workshops
- Speaker
- Fedor Ratnikov
- Year
- 2019
- Language
- English
- Subjects
- Computer science
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed