collaborators

5 papers

astro-ph.GA2025

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…

astro-ph.GA2025

Bridging Simulations and Observations: New Insights into Galaxy Formation Simulations via Out-of-Distribution Detection and Bayesian Model Comparison

Lingyi Zhou, Stefan T. Radev, William H. Oliver +3

Cosmological simulations are a powerful tool to advance our understanding of galaxy formation and many simulations model key properties of real galaxies. A question that naturally…

astro-ph.GA2025

Inferring Galactic Parameters from Chemical Abundances with Simulation-Based Inference

Tobias Buck, Berkay Günes, Giuseppe Viterbo +2

Galactic chemical abundances provide crucial insights into fundamental galactic parameters, such as the high-mass slope of the initial mass function (IMF) and the normalization of…

cs.LG2024

Learning Locally Adaptive Metrics that Enhance Structural Representation with

Christian Kleiber, William H. Oliver, Tobias Buck

We present , a novel unsupervised machine learning pipeline designed to enhance the representation of structure within data via producing a more-informative dista…

astro-ph.GA2024

Galaxy Formation and Evolution via Phase-temporal Clustering with FuzzyCat AstroLink

William H. Oliver, Tobias Buck

We demonstrate how the composition of two unsupervised clustering algorithms, and , makes for a powerful tool when studying galaxy formation…