The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence. - Francisco Villaescusa-Navarro; Shy Genel; Daniel Angles-Alcazar; Leander Thiele; Romeel Dave; Desika Narayanan; Andrina Nicola; Yin Li 009; Pablo Villanueva-Domingo; Benjamin D. Wandelt; David N. Spergel; Rachel S. Somerville; et al. (CoRR, 2021)

The CAMELS project: public data release. - Francisco Villaescusa-Navarro; Shy Genel; Daniel Anglés-Alcázar; Lucia A. Perez; Pablo Villanueva-Domingo; Digvijay Wadekar; Helen Shao; Faizan G. Mohammad; Sultan Hassan; Emily Moser; Erwin T. Lau; Luis Fernando Machado Poletti Valle; et al. (CoRR, 2022)

Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects. - Natalí S. M. de Santi; Francisco Villaescusa-Navarro; L. Raul Abramo; Helen Shao; Lucia A. Perez; Tiago Castro; Yueying Ni; Christopher C. Lovell; Elena Hernandez-Martinez; Federico Marinacci; David N. Spergel; Klaus Dolag; et al. (CoRR, 2023)

LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology. - Matthew Ho; Deaglan J. Bartlett; Nicolas Chartier; Carolina Cuesta-Lázaro; Simon Ding; Axel Lapel; Pablo Lemos; Christopher C. Lovell; T. Lucas Makinen; Chirag Modi 002; Viraj Pandya; Shivam Pandey; et al. (CoRR, 2024)

CosmoBench: A Multiscale, Multiview, Multitask Cosmology Benchmark for Geometric Deep Learning. - Ningyuan Huang; Richard Stiskalek; Jun-Young Lee; Adrian E. Bayer; Charles C. Margossian; Christian Kragh Jespersen; Lucia A. Perez; Lawrence K. Saul; Francisco Villaescusa-Navarro (CoRR, 2025)