Benjamin D. Wandelt

According to our database, Benjamin D. Wandelt authored at least 21 papers between 2015 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Towards Mitigating Systematics in Large-Scale Surveys via Few-Shot Optimal Transport-Based Feature Alignment.

Sultan Hassan, Sambatra Andrianomena, Benjamin D. Wandelt

CoRR, November, 2025

Galactification: painting galaxies onto dark matter only simulations using a transformer-based model.

Shivam Pandey, Christopher C. Lovell, Chirag Modi, Benjamin D. Wandelt

CoRR, November, 2025

Ordered embeddings and intrinsic dimensionalities with information-ordered bottlenecks.

Matthew Ho, Xiaosheng Zhao, Benjamin D. Wandelt

Mach. Learn. Sci. Technol., 2025

2024

Evidence Networks: simple losses for fast, amortized, neural Bayesian model comparison.

Niall Jeffrey, Benjamin D. Wandelt

Mach. Learn. Sci. Technol., March, 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

Hybrid Summary Statistics.

T. Lucas Makinen, Ce Sui, Benjamin D. Wandelt, Natalia Porqueres, Alan Heavens

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

Scaling-laws for Large Time-series Models.

Thomas D. P. Edwards, James Alvey, Justin Alsing, Nam H. Nguyen, Benjamin D. Wandelt

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

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, Viraj Pandya, Shivam Pandey, Lucia A. Perez, Benjamin D. Wandelt, Greg L. Bryan

CoRR, 2024

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

Optimal simulation-based Bayesian decisions.

Justin Alsing, Thomas D. P. Edwards, Benjamin D. Wandelt

CoRR, 2023

Fishnets: Information-Optimal, Scalable Aggregation for Sets and Graphs.

T. Lucas Makinen, Justin Alsing, Benjamin D. Wandelt

CoRR, 2023

Information-Ordered Bottlenecks for Adaptive Semantic Compression.

Matthew Ho, Xiaosheng Zhao, Benjamin D. Wandelt

CoRR, 2023

2022

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, Andrina Nicola, Leander Thiele, Yongseok Jo, Oliver H. E. Philcox, Benjamin D. Oppenheimer, Megan Tillman, ChangHoon Hahn, Neerav Kaushal, Alice Pisani, Matthew Gebhardt, Ana Maria Delgado, Joyce Caliendo, Christina Kreisch, Kaze W. K. Wong, William R. Coulton, Michael Eickenberg, Gabriele Parimbelli, Yueying Ni, Ulrich P. Steinwandel, Valentina La Torre, Romeel Dave, Nicholas Battaglia, Daisuke Nagai, David N. Spergel, Lars Hernquist, Blakesley Burkhart, Desika Narayanan, Benjamin D. Wandelt, Rachel S. Somerville, Greg L. Bryan, Matteo Viel, Yin Li, Vid Irsic, Katarina Kraljic, Mark Vogelsberger

CoRR, 2022

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, Pablo Villanueva-Domingo, Benjamin D. Wandelt, David N. Spergel, Rachel S. Somerville, José Manuel Zorrilla Matilla, Faizan G. Mohammad, Sultan Hassan, Helen Shao, Digvijay Wadekar, Michael Eickenberg, Kaze W. K. Wong, Gabriella Contardo, Yongseok Jo, Emily Moser, Erwin T. Lau, Luis Fernando Machado Poletti Valle, Lucia A. Perez, Daisuke Nagai, Nicholas Battaglia, Mark Vogelsberger

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, Benjamin D. Wandelt, Leander Thiele, Andrina Nicola, José Manuel Zorrilla Matilla, Helen Shao, Sultan Hassan, Desika Narayanan, Romeel Dave, Mark Vogelsberger

CoRR, 2021

Multifield Cosmology with Artificial Intelligence.

Francisco Villaescusa-Navarro, Daniel Anglés-Alcázar, Shy Genel, David N. Spergel, Yin Li, Benjamin D. Wandelt, Andrina Nicola, Leander Thiele, Sultan Hassan, José Manuel Zorrilla Matilla, Desika Narayanan, Romeel Dave, Mark Vogelsberger

CoRR, 2021

2020

Solving high-dimensional parameter inference: marginal posterior densities & Moment Networks.

Niall Jeffrey, Benjamin D. Wandelt

CoRR, 2020

2015

Using hybrid GPU/CPU kernel splitting to accelerate spherical convolutions.

Paul M. Sutter, Benjamin D. Wandelt, Franz Elsner

Astron. Comput., 2015

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