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Consider the problem of matching two independent i.i.d. samples of size $N$ from two distributions $P$ and $Q$ in $\mathbb{R}^d$. For an arbitrary continuous cost function, the optimal assignment problem looks for the matching that…

Probability · Mathematics 2023-01-03 Zaid Harchaoui , Lang Liu , Soumik Pal

The control-affine Schr\"odinger bridge concerns with a stochastic optimal control problem. Its solution is a controlled evolution of joint state probability density subject to a control-affine It\^o diffusion with a given deadline…

We consider the Schr\"odinger bridge problem which, given ensemble measurements of the initial and final configurations of a stochastic dynamical system and some prior knowledge on the dynamics, aims to reconstruct the "most likely"…

Machine Learning · Statistics 2026-02-04 Stephen Y. Zhang , Michael P H Stumpf

A Schr\"{o}dinger bridge establishes a dynamic transport map between two target distributions via a reference process, simultaneously solving an associated entropic optimal transport problem. We consider the setting where samples from the…

Machine Learning · Computer Science 2025-01-22 Stefano Peluchetti

Image inpainting is an important image generation task, which aims to restore corrupted image from partial visible area. Recently, diffusion Schr\"odinger bridge methods effectively tackle this task by modeling the translation between…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Zihao Han , Baoquan Zhang , Lisai Zhang , Shanshan Feng , Kenghong Lin , Guotao Liang , Yunming Ye , Xiaochen Qi , Guangming Ye

This work focuses on stability analysis of numerical solutions to jump diffusions and jump diffusions with Markovian switching. Due to the use of Poisson processes, using asymptotic expansions as in the usual approach of treating diffusion…

Optimization and Control · Mathematics 2014-07-11 Zhixin Yang , G. Yin , Haibo Li

In this paper, we study optimal stochastic control problems for stochastic systems driven by non-Markov sub-diffusion $B_{L_t}$, which have the mixed features of deterministic and stochastic controls. Here $B_t$ is the standard Brownian…

Probability · Mathematics 2023-11-28 Shuaiqi Zhang , Zhen-Qing Chen

We perform a detailed comparison between a Markov Switching Jump Diffusion Model and a Markov Switching {\alpha}-Stable Distribution Model with respect to the analysis of non-stationary data. We show that the jump diffusion model is…

Applications · Statistics 2016-05-20 Luca Di Persio , Vukasin Jovic

This work addresses the problem of optimally steering the state covariance of a linear stochastic system from an initial to a target, subject to hybrid transitions. The nonlinear and discontinuous jump dynamics complicate the control design…

Optimization and Control · Mathematics 2024-10-18 Hongzhe Yu , Diana Frias Franco , Aaron M. Johnson , Yongxin Chen

Density ratio estimation is fundamental to tasks involving $f$-divergences, yet existing methods often fail under significantly different distributions or inadequately overlapping supports -- the density-chasm and the support-chasm…

Machine Learning · Computer Science 2025-11-04 Wei Chen , Shigui Li , Jiacheng Li , Junmei Yang , John Paisley , Delu Zeng

We characterize the Schr\"odinger bridge problems by a family of Mckean-Vlasov stochastic control problems with no terminal time distribution constraint. In doing so, we use the theory of Hilbert space embeddings of probability measures and…

Optimization and Control · Mathematics 2025-12-10 Yumiharu Nakano

We propose Image-to-Image Schr\"odinger Bridge (I$^2$SB), a new class of conditional diffusion models that directly learn the nonlinear diffusion processes between two given distributions. These diffusion bridges are particularly useful for…

Computer Vision and Pattern Recognition · Computer Science 2023-05-29 Guan-Horng Liu , Arash Vahdat , De-An Huang , Evangelos A. Theodorou , Weili Nie , Anima Anandkumar

The Schr\"odinger Bridge (SB) problem offers a powerful framework for combining optimal transport and diffusion models. A promising recent approach to solve the SB problem is the Iterative Markovian Fitting (IMF) procedure, which alternates…

Machine Learning · Computer Science 2024-11-06 Nikita Gushchin , Daniil Selikhanovych , Sergei Kholkin , Evgeny Burnaev , Alexander Korotin

A Schr\"odinger bridge is the most probable time-dependent probability distribution that connects an initial probability distribution $w_{i}$ to a final one $w_{f}$. The problem has been solved and widely used for the case of simple…

Statistical Mechanics · Physics 2025-07-02 Henri Orland

The momentum Schr\"odinger Bridge (mSB) has emerged as a leading method for accelerating generative diffusion processes and reducing transport costs. However, the lack of simulation-free properties inevitably results in high training costs…

Machine Learning · Statistics 2025-01-29 Kevin Rojas , Yixin Tan , Molei Tao , Yuriy Nevmyvaka , Wei Deng

In this work, we study a discrete Schr\"odinger bridge problem with partial marginal observations. A main difficulty compared to the classical Schr\"odinger bridge formulation is that our problem is not strictly convex and standard…

Optimization and Control · Mathematics 2026-04-08 Michele Mascherpa , Victor Molnö , Carsten Skovmose Kallesøe , Johan Karlsson

We propose a general framework for studying jump-diffusion systems driven by both Gaussian noise and a jump process with state-dependent intensity. Of particular natural interest are the jump locations: the system evaluated at the jump…

Statistical Mechanics · Physics 2018-09-28 Christopher E. Miles , James P. Keener

In this article, we discuss subgeometric ergodicity of a class of regime-switching diffusion processes. We derive conditions on the drift and diffusion coefficients, and the switching mechanism which result in subgeometric ergodicity of the…

Probability · Mathematics 2022-04-12 Petra Lazić , Nikola Sandrić

In image generation, Schr\"odinger Bridge (SB)-based methods theoretically enhance the efficiency and quality compared to the diffusion models by finding the least costly path between two distributions. However, they are computationally…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Xingyu Qiu , Mengying Yang , Xinghua Ma , Fanding Li , Dong Liang , Gongning Luo , Wei Wang , Kuanquan Wang , Shuo Li

Diffusion models have become the go-to method for large-scale generative models in real-world applications. These applications often involve data distributions confined within bounded domains, typically requiring ad-hoc thresholding…

Machine Learning · Statistics 2024-01-09 Wei Deng , Yu Chen , Nicole Tianjiao Yang , Hengrong Du , Qi Feng , Ricky T. Q. Chen
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