Deep Recurrent Neural Networks for Supernovae Classification

Cited by (123)

Items 101–123 of 123

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2. Characterizing the Sample Selection for Supernova Cosmology
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3. Characterizing the Sample Selection for Supernova Cosmology
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4. Multivariate time series transformer embeddings for light curves of periodic variable stars
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5. Searching for outliers in the Chandra Source Catalog
   Dustin K. Swarm, Casey T. DeRoo, Y Liu, S Watkins · 2022 · Monthly Notices of the Royal Astronomical Society
6. Time Domain Astroinformatics
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7. Time Series
   Ashish A. Mahabal · 2020 · Elsevier eBooks
8. ATAT: Astronomical Transformer for time series And Tabular data
   Nicolás Astorga, I. Reyes, G. Cabrera-Vives, F. Förster, P. Huijse, Javier Arredondo, Daniel Moreno-Cartagena, A. Muñoz-Arancibia, Amelia Bayo, Márcio Catelan et al. · 2023 · Research Square
9. Deep-Learning the Time Domain
   Ashish A. Mahabal, Kinal Sheth, Fabian Cristian Gieseke, Andrew J Drake, G. Djorgovski, M. J. Graham · 2017 · Proceedings of the International Astronomical Union
10. SuperNNova light-curve simulations
    A. Möller, T. de Boissière · 2019 · Figshare
11. AI detection of S/N<1 sources in infrared images: a deep learning algorithm developed for the AZT24 facility at Campo Imperatore Observatory
    Stefano Di Frischia, Mauro Dolci · 2024 · SPIE Software and Cyberinfrastructure for Astronomy
12. Analysis of methods for optical-band light curves
    Haifeng Yang, Yi Chen, Jiongyu Chen, Lichan Zhou, Jianghui Cai, Yuqing Yang · 2025 · Publications of the Astronomical Society of Japan
13. Non-Gaussian cosmology : theoretical and statistical challenges for modern galaxy surveys
    Matteo Rizzato · 2019
14. Learning salient information with neural networks for cosmological analysis
    Qiufan Lin · 2021 · theses.fr (ABES)
15. Galaxy redshift estimation from multi-band images with deep learning : strengths and challenges
    Mohammed Reda Ait Ouahmed · 2023 · theses.fr (ABES)
16. Empreintes cosmologiques et gravitationnelles de la forme des halos de matière noire : Analyse statistique et apprentissage automatique
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17. An FPCA-enhanced Ensemble Learning Framework for Photometric Identification of Type Ia Supernovae
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18. PIE-ADA: Physics-Informed Ensemble with Adaptive Data Augmentation for Photometric Transient Classification
    Deba Priyo Guha, Fariya Tabassum · 2026 · IEEE International Conference on Quantum Photonics, Artificial Intelligence & Networking (QPAIN)
19. Searching for Type Ia Supernovae in the Dark Energy Spectroscopic Instrument
    Xiaoyu Zhuang, Ran Song, Dezheng Meng, Weiyu Ding, Ranfang Zheng, Yao Yao, Zheyu Lin, Bing-Xue Fu, Fujia Li, Zelin Xu et al. · 2026 · The Astrophysical Journal
20. Supernova Classification Using the Recurrent Neural Network in the CSST Ultra-deep Field Survey
    Minglin Wang, Yan Gong, Dejia Zhou, Xuelei Chen · 2026 · The Astrophysical Journal
21. Compact and physically interpretable feature models for photometric type Ia supernova classification
    Anurag Garg · 2026 · Journal of Astrophysics and Astronomy
22. Human-Informed Neural Networks (HINNs): Trust-Adaptive Learning with Expert Guidance
    Mohammad Behdad Jamshidi · 2026 · Human-Centric Intelligent Systems
23. Interstellar Intelligence: A Survey of AI-Powered Real-Time Detection of Astronomical Events
    A. Angeline, Blessy Louis, V. Sindhu · 2026 · Lecture notes in electrical engineering