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astro-ph.IM2026
Deep Learning for Astrophysics: An Open Textbook from the NASA Cosmic Origins AI/ML Science and Technology Interest Group
Yuan-Sen Ting, Digvijay Wadekar, Phill Cargile +21
Recent community assessments identify education as a principal barrier to adopting modern machine learning in astronomy. We present Deep Learning for Astrophysics, a freely availab…
cs.LG2026
Scale-Aware Adversarial Analysis: A Diagnostic for Generative AI in Multiscale Complex Systems
Mengke Zhao, Guang-Xing Li, Duo Xu +1
Complex physical systems, from supersonic turbulence to the macroscopic structure of the universe, are governed by continuous multiscale dynamics. While modern machine learning arc…
astro-ph.GA2026
Disk Wind Feedback from High-mass Protostars. V. Application of Multi-Modal Machine Learning to Characterize Outflow Properties
Duo Xu, Ioana A. Stelea, Joshua S. Speagle +2
Characterizing protostellar outflows is fundamental to understanding star formation feedback, yet traditional methods are often hindered by projection effects and complex morpholog…