Author

Xingchen Yan

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#artificial intelligence Jun 2026

TransitNet: A Compact Attention-Augmented Deep Learning Framework for Low-SNR Transit Blind Searches

The results demonstrate that TransitNet provides an accurate, scalable, and computationally efficient framework for low-SNR transit blind searches in the tested regime and motivate its extension to longer-period Earth-size planet searches.

Xing-Chen Yan, Jian Ge, Qing-Tian Liu et al. · arXiv.org · 0 citations

#artificial intelligence Preprint May 2026

DELOS: Contrastive Deep Learning for Low-SNR Blind Transit Searches in Kepler Photometry

DELOS provides an efficient and sensitive framework for low-SNR transit searches and represents a practical step toward future searches for longer-period terrestrial planets in Kepler, K2, TESS, PLATO, and Earth 2.0 data.

Qingtian Liu, Jian Ge, Xingchen Yan et al. · 1 citation