5 papers
Simulation-based Inference via Langevin Dynamics with Score Matching
Haoyu Jiang, Yuexi Wang, Yun Yang
Simulation-based inference (SBI) enables Bayesian analysis when the likelihood is intractable but model simulations are available. Recent advances in statistics and machine learnin…
Smooth Calibration and Decision Making
Jason Hartline, Yifan Wu, Yunran Yang
Calibration requires predictor outputs to be consistent with their Bayesian posteriors. For machine learning predictors that do not distinguish between small perturbations, calibra…
Learning Density Evolution from Snapshot Data
Rentian Yao, Atsushi Nitanda, Xiaohui Chen +1
Motivated by learning dynamical structures from static snapshot data, this paper presents a distribution-on-scalar regression approach for estimating the density evolution of a sto…
Wasserstein Proximal Coordinate Gradient Algorithms
Rentian Yao, Xiaohui Chen, Yun Yang
Motivated by approximation Bayesian computation using mean-field variational approximation and the computation of equilibrium in multi-species systems with cross-interaction, this…
Minimizing Convex Functionals over Space of Probability Measures via KL Divergence Gradient Flow
Rentian Yao, Linjun Huang, Yun Yang
Motivated by the computation of the non-parametric maximum likelihood estimator (NPMLE) and the Bayesian posterior in statistics, this paper explores the problem of convex optimiza…