arXiv Machine Learning June 10, 2026 By Ludvig Doeser, Jens Jasche

Learning the Universe: Posterior Reliability of Neural Generative Models in High-Dimensional Field-Level Inference of Cosmic Initial Conditions

Read the original on arXiv Machine Learning →

arXiv:2606. 10023v1 Announce Type: cross Abstract: Accurate posterior estimation is central to scientific inference, as uncertainties determine what can be reliably learned from observational data.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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