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20082023
most citedA Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems

212 citations · 625 across the 54 of their papers we have counts for

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Showing 2018Show all

8 papers · 1 filter

stat.CO2018★ 14 cited

Multilevel Optimal Transport: a Fast Approximation of Wasserstein-1 distances

Jialin Liu, Wotao Yin, Wuchen Li +1

We propose a fast algorithm for the calculation of the Wasserstein-1 distance, which is a particular type of optimal transport distance with homogeneous of degree one transport cos…

math.ST2018★ 17 cited

Ricci curvature for parametric statistics via optimal transport

Wuchen Li, Guido Montufar

We elaborate the notion of a Ricci curvature lower bound for parametrized statistical models. Following the seminal ideas of Lott-Strum-Villani, we define this notion based on the…

math.OC2018★ 4 cited

Constrained dynamical optimal transport and its Lagrangian formulation

Wuchen Li, Stanley Osher

We propose dynamical optimal transport (OT) problems constrained in a parameterized probability subset. In application problems such as deep learning, the probability distribution…

math.OC2018

Solving Large-Scale Optimization Problems with a Convergence Rate Independent of Grid Size

Matt Jacobs, Flavien Léger, Wuchen Li +1

We present a primal-dual method to solve L1-type non-smooth optimization problems independently of the grid size. We apply these results to two important problems : the Rudin-Osher…

math.NA2018★ 6 cited

Algorithm for Hamilton-Jacobi equations in density space via a generalized Hopf formula

Yat Tin Chow, Wuchen Li, Stanley Osher +1

We design fast numerical methods for Hamilton-Jacobi equations in density space (HJD), which arises in optimal transport and mean field games. We overcome the curse-of-infinite-dim…

math.OC2018★ 10 cited

Optimal transport natural gradient for statistical manifolds with continuous sample space

Yifan Chen, Wuchen Li

We study the Wasserstein natural gradient in parametric statistical models with continuous sample spaces. Our approach is to pull back the -Wasserstein metric tensor in the pr…

math.OC2018★ 4 cited

Natural gradient via optimal transport

Wuchen Li, Guido Montufar

We study a natural Wasserstein gradient flow on manifolds of probability distributions with discrete sample spaces. We derive the Riemannian structure for the probability simplex f…

math.DG2018★ 31 cited

Transport information geometry I: Riemannian calculus on probability simplex

Wuchen Li

We formulate the Riemannian calculus of the probability set embedded with -Wasserstein metric. This is an initial work of transport information geometry. Our investigation sta…