9 citations · 42 across the 18 of their papers we have counts for
4 papers · 1 filter
Optimal Neural Network Approximation of Wasserstein Gradient Direction via Convex Optimization
Yifei Wang, Peng Chen, Mert Pilanci +1
The computation of Wasserstein gradient direction is essential for posterior sampling problems and scientific computing. The approximation of the Wasserstein gradient with finite s…
Projected Wasserstein gradient descent for high-dimensional Bayesian inference
Yifei Wang, Peng Chen, Wuchen Li
We propose a projected Wasserstein gradient descent method (pWGD) for high-dimensional Bayesian inference problems. The underlying density function of a particle system of WGD is a…
Wasserstein Proximal of GANs
Alex Tong Lin, Wuchen Li, Stanley Osher +1
We introduce a new method for training generative adversarial networks by applying the Wasserstein-2 metric proximal on the generators. The approach is based on Wasserstein informa…
Wasserstein Diffusion Tikhonov Regularization
Alex Tong Lin, Yonatan Dukler, Wuchen Li +1
We propose regularization strategies for learning discriminative models that are robust to in-class variations of the input data. We use the Wasserstein-2 geometry to capture seman…