63 citations · 224 across the 12 of their papers we have counts for
4 papers · 1 filter
Hybrid Summary Statistics
T. Lucas Makinen, Ce Sui, Benjamin D. Wandelt +2
We present a way to capture high-information posteriors from training sets that are sparsely sampled over the parameter space for robust simulation-based inference. In physical inf…
CHARM: Creating Halos with Auto-Regressive Multi-stage networks
Shivam Pandey, Chirag Modi, Benjamin D. Wandelt +7
To maximize the amount of information extracted from cosmological datasets, simulations that accurately represent these observations are necessary. However, traditional simulations…
Optimal Neural Summarisation for Full-Field Weak Lensing Cosmological Implicit Inference
Denise Lanzieri, Justine Zeghal, T. Lucas Makinen +3
Traditionally, weak lensing cosmological surveys have been analyzed using summary statistics motivated by their analytically tractable likelihoods, or by their ability to access hi…
LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology
Matthew Ho, Deaglan J. Bartlett, Nicolas Chartier +12
This paper presents the Learning the Universe Implicit Likelihood Inference (LtU-ILI) pipeline, a codebase for rapid, user-friendly, and cutting-edge machine learning (ML) inferenc…