15 citations · 23 across the 6 of their papers we have counts for
6 papers
Machine Learning and the SKA for Cosmic Dawn and the Epoch of Reionization
Anshuman Acharya, Michele Bianco, Daniela Breitman +18
When operational, the SKA will generate unprecedented amounts of data and provide exquisite sensitivity for 21 cm tomography of Cosmic Dawn (CD) and the Epoch of Reionization (EoR)…
How to evaluate the sufficiency and complementarity of summary statistics for cosmic fields: an information-theoretic perspective
Ce Sui, Yi Mao, Xiaosheng Zhao +2
The advent of increasingly advanced surveys and cosmic tracers has motivated the development of new inference techniques and novel approaches to extracting information from cosmic…
Fisher Score Matching for Simulation-Based Forecasting and Inference
Ce Sui, Shivam Pandey, Benjamin D. Wandelt
We propose a method for estimating the Fisher score--the gradient of the log-likelihood with respect to model parameters--using score matching. By introducing a latent parameter mo…
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 +3
Current and future large scale structure surveys aim to constrain the neutrino mass and the equation of state of dark energy. We aim to construct accurate and interpretable symboli…
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…
Evaluating Summary Statistics with Mutual Information for Cosmological Inference
Ce Sui, Xiaosheng Zhao, Tao Jing +1
The ability to compress observational data and accurately estimate physical parameters relies heavily on informative summary statistics. In this paper, we introduce the use of mutu…