collaborators

9 papers

math.OC2026

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…

math.OC2026

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…

cs.LG2026

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…

math.OC2026

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…

cs.LG2025

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…

math.OC2025

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…