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stat.ML2022★ 1 cited
Projected Gradient Descent Algorithms for Solving Nonlinear Inverse Problems with Generative Priors
Zhaoqiang Liu, Jun Han
In this paper, we propose projected gradient descent (PGD) algorithms for signal estimation from noisy nonlinear measurements. We assume that the unknown -dimensional signal lie…
stat.ML2018
Stein Variational Gradient Descent Without Gradient
Jun Han, Qiang Liu
Stein variational gradient decent (SVGD) has been shown to be a powerful approximate inference algorithm for complex distributions. However, the standard SVGD requires calculating…