Synthetic Gaia DR2

Synthetic Gaia DR2 data serves as a crucial testbed for developing and evaluating various AI models, primarily focusing on improving the accuracy and efficiency of data analysis and generation tasks. Current research emphasizes the use of deep learning architectures, including neural networks and tree-based algorithms, for tasks such as stellar parameter estimation, out-of-distribution detection, and generative modeling of astronomical phenomena. This work is significant because it allows researchers to explore complex astrophysical problems and benchmark AI capabilities in a controlled environment, ultimately advancing both astronomical understanding and AI methodology.