9 papers
Distribution Steering via Sliced Optimal Transport Control
Kaito Ito, Anqi Dong
Distribution steering seeks feedback laws that drive the state law of a dynamical system between prescribed initial and terminal distributions. Optimal transport provides a natural…
Sliced Wasserstein Steering between Gaussian Measures
Kaito Ito, Anqi Dong
Optimal transport with quadratic cost provides a geometric framework for steering an ensemble, modeled by a probability law, with minimal effort. Yet ambient-space formulations bec…
Learning Sampled-data Control for Swarms via MeanFlow
Anqi Dong, Yongxin Chen, Karl H. Johansson +1
Steering large-scale swarms with only limited control updates is often needed due to communication or computational constraints, yet most learning-based approaches do not account f…
Temporally Flexible Transport Scheduling on Networks with Departure-Arrival Constriction and Nodal Capacity Limits
Anqi Dong, Karl H. Johansson, Johan Karlsson
We investigate the optimal transport (OT) problem over networks, wherein supply and demand are conceptualized as temporal marginals governing departure rates of particles from sour…
Optimization of continuous-flow over traffic networks with fundamental diagram constraints
Anqi Dong, Karl Henrik Johansson, Johan Karlsson
Optimal transport (OT) theory provides a principled framework for modeling mass movement in applications such as mobility, logistics, and economics. Classical formulations, however…
Federated Flow Matching
Zifan Wang, Anqi Dong, Mahmoud Selim +2
Data today is decentralized, generated and stored across devices and institutions where privacy, ownership, and regulation prevent centralization. This motivates the need to train…
OAT-FM: Optimal Acceleration Transport for Improved Flow Matching
Angxiao Yue, Anqi Dong, Hongteng Xu
As a powerful technique in generative modeling, Flow Matching (FM) aims to learn velocity fields from noise to data, which is often explained and implemented as solving Optimal Tra…
Fundamental diagram constrained dynamic optimal transport via proximal splitting methods
Anqi Dong, Karl Henrik Johansson, Johan Karlsson
Optimal transport has recently been brought forward as a tool for modeling and efficiently solving a variety of flow problems, such as origin-destination problems and multi-commodi…
Task Allocation for Multi-agent Systems via Unequal-dimensional Optimal Transport
Anqi Dong, Karl H. Johansson, Johan Karlsson
We consider a probabilistic model for large-scale task allocation problems for multi-agent systems, aiming to determine an optimal deployment strategy that minimizes the overall tr…