48 citations · 303 across the 37 of their papers we have counts for
5 papers · 1 filter
Graph-structured tensor optimization for nonlinear density control and mean field games
Axel Ringh, Isabel Haasler, Yongxin Chen +1
In this work we develop a numerical method for solving a type of convex graph-structured tensor optimization problems. This type of problems, which can be seen as a generalization…
Quantifying and Computing Covariance Uncertainty
Filip Elvander, Johan Karlsson, Toon van Waterschoot
In this work, we consider the problem of bounding the values of a covariance function corresponding to a continuous-time stationary stochastic process or signal. Specifically, for…
On the complexity of the optimal transport problem with graph-structured cost
Jiaojiao Fan, Isabel Haasler, Johan Karlsson +1
Multi-marginal optimal transport (MOT) is a generalization of optimal transport to multiple marginals. Optimal transport has evolved into an important tool in many machine learning…
Scalable computation of dynamic flow problems via multi-marginal graph-structured optimal transport
Isabel Haasler, Axel Ringh, Yongxin Chen +1
In this work, we develop a new framework for dynamic network flow problems based on optimal transport theory. We show that the dynamic multi-commodity minimum-cost network flow pro…
Mixed-Spectrum Signals -- Discrete Approximations and Variance Expressions for Covariance Estimates
Filip Elvander, Johan Karlsson
The estimation of the covariance function of a stochastic process, or signal, is of integral importance for a multitude of signal processing applications. In this work, we derive c…