9 papers
Lifted Schrödinger Bridges for Gaussian Mixture Endpoints: Projection Gaps and Path-Space Obstructions
Siddhartha Ganguly, George Rapakoulias, Panagiotis Tsiotras
We study stochastic density control between Gaussian-mixture endpoint distributions under Brownian prior dynamics. Since the direct Schrödinger bridge between Gaussian mixtures is…
Stochastic Transition-Map Distillation for Fast Probabilistic Inference
George Rapakoulias, Peter Garud, Lingjiong Zhu +1
Diffusion models achieve strong generation quality, diversity, and distribution coverage, but their performance often comes with expensive inference. In this work, we propose Stoch…
Nonlinear Stochastic Density Steering via Gaussian Mixture Schrodinger Bridges and Multiple Linearizations
Mattia Mosso, George Rapakoulias, Yue Guan +1
The paper studies the optimal density steering problem for nonlinear continuous-time stochastic systems. To accurately capture nonlinear dynamics in high-uncertainty regions that d…
Schrodinger Bridges and Density Steering Problems for Gaussian Mixtures Models in Discrete-Time
George Rapakoulias, Fengjiao Liu, Panagiotis Tsiotras
In this work, we revisit the discrete-time Schrödinger Bridge (SB) and Density Steering (DS) problems for Gaussian mixture model (GMM) boundary distributions. Building on the exis…
Go With the Flow: Fast Diffusion for Gaussian Mixture Models
George Rapakoulias, Ali Reza Pedram, Fengjiao Liu +2
Schrodinger Bridges (SBs) are diffusion processes that steer, in finite time, a given initial distribution to another final one while minimizing a suitable cost functional. Althoug…
Steering Large Agent Populations using Mean-Field Schrodinger Bridges with Gaussian Mixture Models
George Rapakoulias, Ali Reza Pedram, Panagiotis Tsiotras
The Mean-Field Schrodinger Bridge (MFSB) problem is an optimization problem aiming to find the minimum effort control policy to drive a McKean-Vlassov stochastic differential equat…