arXiv Machine Learning June 11, 2026 By Federico Semenzato, Benjamin D. Wandelt, Michele Liguori, Alvise Raccanelli

Interpretable Neural Marked Statistics for Cosmological Inference

Read the original on arXiv Machine Learning →

arXiv:2606. 11295v1 Announce Type: cross Abstract: Recovering cosmological information beyond the power spectrum is a central goal for upcoming cosmological surveys, since late-time non-Gaussian signal in the matter density cannot be accessed through two-point statistics alone.

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

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