VIDE: The Void IDentification and Examination toolkit. - Paul M. Sutter; Guilhem Lavaux; Nico Hamaus; Alice Pisani; Benjamin D. Wandelt; Michael S. Warren; Francisco Villaescusa-Navarro; Paul Zivick; Qingqing Mao; Benjamin B. Thompson (Astron. Comput., 2015)

Using hybrid GPU/CPU kernel splitting to accelerate spherical convolutions. - Paul M. Sutter; Benjamin D. Wandelt; Franz Elsner (Astron. Comput., 2015)

Solving high-dimensional parameter inference: marginal posterior densities & Moment Networks. - Niall Jeffrey; Benjamin D. Wandelt (CoRR, 2020)

Multifield Cosmology with Artificial Intelligence. - Francisco Villaescusa-Navarro; Daniel Anglés-Alcázar; Shy Genel; David N. Spergel; Yin Li 009; Benjamin D. Wandelt; Andrina Nicola; Leander Thiele; Sultan Hassan; José Manuel Zorrilla Matilla; Desika Narayanan; Romeel Dave; et al. (CoRR, 2021)

Robust marginalization of baryonic effects for cosmological inference at the field level. - Francisco Villaescusa-Navarro; Shy Genel; Daniel Angles-Alcazar; David N. Spergel; Yin Li 009; Benjamin D. Wandelt; Leander Thiele; Andrina Nicola; José Manuel Zorrilla Matilla; Helen Shao; Sultan Hassan; Desika Narayanan; et al. (CoRR, 2021)

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)

Information-Ordered Bottlenecks for Adaptive Semantic Compression. - Matthew Ho; Xiaosheng Zhao; Benjamin D. Wandelt (CoRR, 2023)

Fishnets: Information-Optimal, Scalable Aggregation for Sets and Graphs. - T. Lucas Makinen; Justin Alsing; Benjamin D. Wandelt (CoRR, 2023)

Optimal simulation-based Bayesian decisions. - Justin Alsing; Thomas D. P. Edwards; Benjamin D. Wandelt (CoRR, 2023)

A precise symbolic emulator of the linear matter power spectrum. - Deaglan J. Bartlett; Lukas Kammerer; Gabriel Kronberger; Harry Desmond; Pedro G. Ferreira; Benjamin D. Wandelt; Bogdan Burlacu; David Alonso; Matteo Zennaro (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)

syren-halofit: A fast, interpretable, high-precision formula for the ΛCDM nonlinear matter power spectrum. - Deaglan J. Bartlett; Benjamin D. Wandelt; Matteo Zennaro; Pedro G. Ferreira; Harry Desmond (CoRR, 2024)

Scaling-laws for Large Time-series Models. - Thomas D. P. Edwards; James Alvey; Justin Alsing; Nam H. Nguyen; Benjamin D. Wandelt (CoRR, 2024)

Hybrid summary statistics: neural weak lensing inference beyond the power spectrum. - T. Lucas Makinen; Alan Heavens; Natalia Porqueres; Tom Charnock; Axel Lapel; Benjamin D. Wandelt (CoRR, 2024)

Hybrid Summary Statistics. - T. Lucas Makinen; Ce Sui; Benjamin D. Wandelt; Natalia Porqueres; Alan Heavens (CoRR, 2024)

syren-new: Precise formulae for the linear and nonlinear matter power spectra with massive neutrinos and dynamical dark energy. - Ce Sui; Deaglan J. Bartlett; Shivam Pandey; Harry Desmond; Pedro G. Ferreira; Benjamin D. Wandelt (CoRR, 2024)

Evidence Networks: simple losses for fast, amortized, neural Bayesian model comparison. - Niall Jeffrey; Benjamin D. Wandelt (Mach. Learn. Sci. Technol., 2024)