10 citations · 16 across the 4 of their papers we have counts for
7 papers
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…
Incremental inference of collective graphical models
Rahul Singh, Isabel Haasler, Qinsheng Zhang +2
We consider incremental inference problems from aggregate data for collective dynamics. In particular, we address the problem of estimating the aggregate marginals of a Markov chai…
Multi-marginal optimal transport and probabilistic graphical models
Isabel Haasler, Rahul Singh, Qinsheng Zhang +2
We study multi-marginal optimal transport problems from a probabilistic graphical model perspective. We point out an elegant connection between the two when the underlying cost for…
Multi-marginal Optimal Transport with a Tree-structured cost and the Schrödinger Bridge Problem
Isabel Haasler, Axel Ringh, Yongxin Chen +1
The optimal transport problem has recently developed into a powerful framework for various applications in estimation and control. Many of the recent advances in the theory and app…
Inference with Aggregate Data: An Optimal Transport Approach
Rahul Singh, Isabel Haasler, Qinsheng Zhang +2
We consider inference (filtering) problems over probabilistic graphical models with aggregate data generated by a large population of individuals. We propose a new efficient belief…
Multi-Marginal Optimal Mass Transport with Partial Information
Filip Elvander, Isabel Haasler, Andreas Jakobsson +1
During recent decades, there has been a substantial development in optimal mass transport theory and methods. In this work, we consider multi-marginal problems wherein only partial…