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🇧🇾 Belarus national stage 2026, National stage (Minsk, 31 Mar to 2 Apr 2026)
Transient Detection by Difference Imaging (ATLAS)
Classify ATLAS new/reference/difference image triplets as real transients or artefacts, using all three frames, scored by F2 (recall weighted).
- Statement
- Russian · Read it in English (Google Translate)
- To hand in
- A trained model
- Hardware
- Needs a GPU (free Colab works)
- Data size
- 509 MB
- Data type
- 🖼️ Images
- Estimated difficulty
- Unknown
Get ready on the platform
The foundations of the learning path for this kind of data.
›How to tackle it
- Read the statement. What to hand in, the metric that scores you, the time and hardware limits.
- Explore the data. Size, format, missing values, how the labels are spread.
- Score yourself first. Keep part of the training data aside to measure your work before submitting.
- Start simple, then improve. A first solution that works end to end, then one change at a time.
- Compare with a solution. Once you have searched, open it and see what you would have done differently.
Unofficial copy: the organisers' original may differ.
The statement, data and solutions belong to their authors; we only link to them. Licence : Apache-2.0.
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