5 papers
Global polynomial-time estimation in statistical nonlinear inverse problems via generalized stability
Sven Wang
Non-linear statistical inverse problems pose major challenges both for statistical analysis and computation. Likelihood-based estimators typically lead to non-convex and possibly m…
Statistical algorithms for low-frequency diffusion data: A PDE approach
Matteo Giordano, Sven Wang
We consider the problem of making nonparametric inference in a class of multi-dimensional diffusions in divergence form, from low-frequency data. Statistical analysis in this setti…
Distributionally Robust Gaussian Process Regression and Bayesian Inverse Problems
Xuhui Zhang, Jose Blanchet, Youssef Marzouk +2
We study a distributionally robust optimization formulation (i.e., a min-max game) for two representative problems in Bayesian nonparametric estimation: Gaussian process regression…
Statistical Learning Theory for Neural Operators
Niklas Reinhardt, Sven Wang, Jakob Zech
We present statistical convergence results for the learning of (possibly) non-linear mappings in infinite-dimensional spaces. Specifically, given a map $G_0:\mathcal X\to\mathcal Y…
Wasserstein-based Minimax Estimation of Dependence in Multivariate Regularly Varying Extremes
Xuhui Zhang, Jose Blanchet, Youssef Marzouk +2
We present the first minimax risk bounds for estimators of the spectral measure in multivariate linear factor models, where observations are linear combinations of regularly varyin…