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Related papers: Schrodinger Bridge over Averaged Systems

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We show that the minimum effort control of colloidal self-assembly can be naturally formulated in the order-parameter space as a generalized Schr\"{o}dinger bridge problem -- a class of fixed-horizon stochastic optimal control problems that…

Optimization and Control · Mathematics 2023-10-17 Iman Nodozi , Charlie Yan , Mira Khare , Abhishek Halder , Ali Mesbah

Trajectory optimization is a fundamental stochastic optimal control problem. This paper deals with a trajectory optimization approach for dynamical systems subject to measurement noise that can be fitted into linear time-varying stochastic…

Systems and Control · Electrical Eng. & Systems 2021-08-24 Prakash Mallick , Zhiyong Chen

In this paper, we study the Schr\"odinger Bridge Problem (SBP), which is central to entropic optimal transport. For general reference processes and begin--endpoint distributions, we propose a forward-reverse iterative Monte Carlo procedure…

Machine Learning · Statistics 2025-07-02 Denis Belomestny , John. Schoenmakers

Progressively applying Gaussian noise transforms complex data distributions to approximately Gaussian. Reversing this dynamic defines a generative model. When the forward noising process is given by a Stochastic Differential Equation (SDE),…

Machine Learning · Statistics 2023-04-06 Valentin De Bortoli , James Thornton , Jeremy Heng , Arnaud Doucet

Exploiting a fluid dynamic formulation for which a probabilistic counterpart might not be available, we extend the theory of Schroedinger bridges to the case of inertial particles with losses and general, possibly singular diffusion…

Mathematical Physics · Physics 2014-10-08 Yongxin Chen , Tryphon T. Georgiou , Michele Pavon

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

We consider the problem of sampling transition paths between two given metastable states of a molecular system, e.g. a folded and unfolded protein or products and reactants of a chemical reaction. Due to the existence of high energy…

Biomolecules · Quantitative Biology 2023-07-19 Lars Holdijk , Yuanqi Du , Ferry Hooft , Priyank Jaini , Bernd Ensing , Max Welling

This paper considers the problem of randomized influence maximization over a Markovian graph process: given a fixed set of nodes whose connectivity graph is evolving as a Markov chain, estimate the probability distribution (over this fixed…

Social and Information Networks · Computer Science 2017-11-10 Buddhika Nettasinghe , Vikram Krishnamurthy

How to steer a given joint state probability density function to another over finite horizon subject to a controlled stochastic dynamics with hard state (sample path) constraints? In applications, state constraints may encode safety…

Optimization and Control · Mathematics 2020-04-07 Kenneth F. Caluya , Abhishek Halder

The paper studies the optimal density steering problem for nonlinear continuous-time stochastic systems. To accurately capture nonlinear dynamics in high-uncertainty regions that deviate significantly from a nominal linearization point, we…

Systems and Control · Electrical Eng. & Systems 2026-04-27 Mattia Mosso , George Rapakoulias , Yue Guan , Panagiotis Tsiotras

We establish large deviations for dynamical Schr\"{o}dinger problems driven by perturbed Brownian motions when the noise parameter tends to zero. Our results show that Schr\"{o}dinger bridges charge exponentially small masses outside the…

Probability · Mathematics 2026-01-14 Kengo Kato

The bridge problem is to find an SDE (or sometimes an ODE) that bridges two given distributions. The application areas of the bridge problem are enormous, among which the recent generative modeling (e.g., conditional or unconditional image…

Machine Learning · Computer Science 2025-09-15 Minyoung Kim

Given two boundary distributions, the Schr\"odinger Bridge (SB) problem seeks the ``most likely`` random evolution between them with respect to a reference process. It has revealed rich connections to recent machine learning methods for…

Machine Learning · Computer Science 2025-06-03 Maosheng Yang

In this paper we set up an optimal control framework for a hybrid stochastic system with dual or multiple Markov switching diffusion processes, while Markov chains governing these switching diffusions are not identical as assumed by the…

Optimization and Control · Mathematics 2020-11-02 Jianmin Shi

Transporting between arbitrary distributions is a fundamental goal in generative modeling. Recently proposed diffusion bridge models provide a potential solution, but they rely on a joint distribution that is difficult to obtain in…

Machine Learning · Computer Science 2025-03-03 Jun Hyeong Kim , Seonghwan Kim , Seokhyun Moon , Hyeongwoo Kim , Jeheon Woo , Woo Youn Kim

In this paper, we show a large deviation principle for certain sequences of static Schr\"{o}dinger bridges, typically motivated by a scale-parameter decreasing towards zero, extending existing large deviation results to cover a wider range…

Probability · Mathematics 2025-06-23 Viktor Nilsson , Pierre Nyquist

In this paper, we consider the problem of real-time transmission scheduling over time-varying channels. We first formulate the transmission scheduling problem as a Markov decision process (MDP) and systematically unravel the structural…

Machine Learning · Computer Science 2010-03-15 Fangwen Fu , Mihaela van der Schaar

In 1931/32, Schroedinger studied a hot gas Gedankenexperiment, an instance of large deviations of the empirical distribution and an early example of the so-called maximum entropy inference method. This so-called Schroedinger bridge problem…

Optimization and Control · Mathematics 2020-11-30 Yongxin Chen , Tryphon T. Georgiou , Michele Pavon

We reassess the concept of transition at minimum work in classical stochastic finite-time thermodynamics, when the system dynamics is modelled by a diffusion process. We show that a well-posed formulation of the optimal control problem…

Statistical Mechanics · Physics 2026-03-13 Paolo Muratore-Ginanneschi , Julia Sanders

We present simulation-free score and flow matching ([SF]$^2$M), a simulation-free objective for inferring stochastic dynamics given unpaired samples drawn from arbitrary source and target distributions. Our method generalizes both the…