3 citations · 5 across the 7 of their papers we have counts for
5 papers · 1 filter
Self-Supervised Representation Learning for JWST Galaxy Images and Low Resolution Spectra
Yang Cheng, Morgan Fouesneau, Ivelina G. Momcheva +2
A self-supervised multimodal model recovers galaxy stellar masses from sparse JWST data that lack the multi-band coverage required by traditional SED fitting. We train on single-ba…
RUBIX: Differentiable forward modelling of galaxy spectral data cubes for gradient-based parameter estimation
Anna Lena Schaible, Ufuk Çakır, Tobias Buck +5
Although integral-field spectroscopy enables spatially resolved spectral studies of galaxies, bridging particle-based simulations to observations remains slow and non-differentiabl…
Causal Discovery of Latent Variables in Galactic Archaeology
Zehao Jin, Yuxi Lu, Yuan-Sen Ting +2
Galactic archaeology--the study of stellar migration histories--provides insights into galaxy formation and evolution. However, establishing causal relationships between observable…
MEGS: Morphological Evaluation of Galactic Structure
Ufuk Çakır, Tobias Buck
Understanding the morphology of galaxies is a critical aspect of astrophysics research, providing insight into the formation, evolution, and physical properties of these vast cosmi…
GAMMA: Galactic Attributes of Mass, Metallicity, and Age Dataset
Ufuk Çakır, Tobias Buck
We introduce the GAMMA (Galactic Attributes of Mass, Metallicity, and Age) dataset, a comprehensive collection of galaxy data tailored for Machine Learning applications. This datas…