Publications (59)
EigenVI: score-based variational inference with orthogonal function expansions
Diana Cai, Chirag Modi, Charles C. Margossian +3
We develop EigenVI, an eigenvalue-based approach for black-box variational inference (BBVI). EigenVI constructs its variational approximations from orthogonal function expansions.…
Delayed rejection Hamiltonian Monte Carlo for sampling multiscale distributions
Chirag Modi, Alex Barnett, Bob Carpenter
The efficiency of Hamiltonian Monte Carlo (HMC) can suffer when sampling a distribution with a wide range of length scales, because the small step sizes needed for stability in hig…
Joint velocity and density reconstruction of the Universe with nonlinear differentiable forward modeling
Adrian E. Bayer, Chirag Modi, Simone Ferraro
Reconstructing the initial conditions of the Universe from late-time observations has the potential to optimally extract cosmological information. Due to the high dimensionality of…
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…
: Mock Challenge for a Forward Modeling Approach to Galaxy Clustering
ChangHoon Hahn, Michael Eickenberg, Shirley Ho +7
Simulation-Based Inference of Galaxies () is a forward modeling framework for analyzing galaxy clustering using simulation-based inference. In this work…
Modeling Galaxy Surveys with Hybrid SBI
Gemma Zhang, Chirag Modi, Oliver H. E. Philcox
Simulation-based inference (SBI) has emerged as a powerful tool for extracting cosmological information from galaxy surveys deep into the non-linear regime. Despite its great promi…