Software Open Access
CTLearn: Deep learning for imaging atmospheric Cherenkov telescopes event reconstruction
Brill, Ari;
Kim, Bryan;
Nieto, Daniel;
Miener, Tjark;
Feng, Qi
Researcher(s)
Sevilla, JaimeCTLearn is a high-level Python package providing a backend for training deep learning models for the reconstruction of imaging atmospheric Cherenkov telescope events using TensorFlow.
Files
(1.1 MB)
| Name | Size | |
|---|---|---|
|
ctlearn-project/ctlearn-v0.6.1.zip
md5:b4406f57ea75467c8381534bc28cfebf |
1.1 MB | Download |
691
193
views
downloads
| All versions | This version | |
|---|---|---|
| Views | 691 | 97 |
| Downloads | 193 | 154 |
| Data volume | 192.4 MB | 164.2 MB |
| Unique views | 473 | 71 |
| Unique downloads | 176 | 145 |
Indexed in
- Publication date:
- March 18, 2018
- DOI:
-
- Keyword(s):
- Imaging atmospheric Cherenkov telescopes Deep learning High energy physics Event reconstruction
- Grants:
-
European Commission:
- ESCAPE - European Science Cluster of Astronomy & Particle physics ESFRI research infrastructures (824064)
- Related identifiers:
- Derived from
- License (for files):
- BSD 3-Clause "New" or "Revised" License