ĀLOKA - A Rapid and Efficient Optical Transients Identification Framework
Peng Jia
The provided code, a Dockerized implementation of the framework detailed in "A Rapid and Efficient Optical Transients Identification Framework based on Multimodal Neural Network and Machine Learning Operations," can be directly deployed on Linux systems. It serves as a foundational resource for establishing comprehensive services, from the initial detection and analysis of optical transients to their subsequent verification and the integration of MLOps practices.
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Paper Information
Paper Title:
A Rapid and Efficient Optical Transients Identification Framework based on Multimodal Neural Network and Machine Learning Operations
Publication:
ApJs
Identifiers
CSTR:
11379.11.101641
DOI:
10.12149/101641
VO Identifier:
ivo://China-VO/paperdata/101641
Publication Date:
2025-08-01
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Citations
Peng Jia et al. 2025. ĀLOKA - A Rapid and Efficient Optical Transients Identification Framework. Version 1.0. https://doi.org/10.12149/101641
@misc{10.12149/101641,
doi = {10.12149/101641},
url = {https://doi.org/10.12149/101641},
author = {Peng Jia},
title = {ĀLOKA - A Rapid and Efficient Optical Transients Identification Framework },
version = {1.0},
publisher = {Nataional Astronomical Data Center of China},
year= {2025}
}
doi = {10.12149/101641},
url = {https://doi.org/10.12149/101641},
author = {Peng Jia},
title = {ĀLOKA - A Rapid and Efficient Optical Transients Identification Framework },
version = {1.0},
publisher = {Nataional Astronomical Data Center of China},
year= {2025}
}
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This DOI represents all versions, and will always resolve to the latest one.
2025-08-01