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The Schr\"{o}dinger problem of deducing the microscopic dynamics from the input-output statistics data is known to admit a solution in terms of Markov diffusions. The uniqueness of solution is found linked to the natural boundaries…

Quantum Physics · Physics 2008-12-18 Ph. Blanchard , P. Garbaczewski

Bass and Pardoux (1987) deduce from the Krein-Rutman theorem a reverse ergodic theorem for a sub-probability transition function, which turns out to be a key tool in proving uniqueness of reflecting Brownian Motion in cones in Kwon and…

Probability · Mathematics 2024-08-15 Cristina Costantini , Thomas G. Kurtz

The process of diffusion is the most elementary stochastic transport process. Brownian motion, the representative model of diffusion, played a important role in the advancement of scientific fields such as physics, chemistry, biology and…

Statistical Mechanics · Physics 2015-08-11 Alexandre Bovet

Inference-time alignment for diffusion models aims to adapt a pre-trained reference diffusion model toward a target distribution without retraining the reference score network, thereby preserving the generative capacity of the reference…

Machine Learning · Statistics 2026-02-05 Jinyuan Chang , Chenguang Duan , Yuling Jiao , Yi Xu , Jerry Zhijian Yang

In this paper we intend to give a comprehensive approach of functional inequalities for diffusion processes under some "curvature" assumptions. Our notion of curvature coincides with the usual $\Gamma_2$ curvature of Bakry and Emery in the…

Probability · Mathematics 2013-03-28 Patrick Cattiaux , Arnaud Guillin

Our investigation is specially motivated by the stochastic version of a common model of potential spread in a dendritic tree. We do not assume the noise in the junction points to be Markovian. In fact, we allow for long-range dependence in…

Probability · Mathematics 2018-12-21 Stefano Bonaccorsi , Delio Mugnolo

The scope of this paper is generative modeling through diffusion processes. An approach falling within this paradigm is the work of Song et al. (2021), which relies on a time-reversal argument to construct a diffusion process targeting the…

Machine Learning · Computer Science 2023-12-25 Stefano Peluchetti

Reaction-diffusion systems have been proposed as a model for pattern formation and morphogenesis. The Fickian diffusion typically employed in these constructions model the Brownian motion of particles. The biological and chemical elements…

Quantitative Methods · Quantitative Biology 2023-11-09 Siddhartha Srivastava , Krishna Garikipati

We prove the existence of solutions to a non-linear, non-local, degenerate equation which was previously derived as the formal hydrodynamic limit of an active Brownian particle system, where the particles are endowed with a position and an…

Analysis of PDEs · Mathematics 2023-10-02 Martin Burger , Simon Schulz

We provide a class of diffusion processes for continuous time-varying multivariate angular data with explicit transition probability densities, enabling exact likelihood inference. The presented diffusions are time-reversible and can be…

Methodology · Statistics 2024-09-05 Eduardo García-Portugués , Michael Sørensen

When the unconditioned process is a diffusion living on the half-line $x \in ]-\infty,a[$ in the presence of an absorbing boundary condition at position $x=a$, we construct various conditioned processes corresponding to finite or infinite…

Statistical Mechanics · Physics 2022-10-17 Cécile Monthus , Alain Mazzolo

Motivated by queues with many servers, we study Brownian steady-state approximations for continuous time Markov chains (CTMCs). Our approximations are based on diffusion models (rather than a diffusion limit) whose steady-state, we prove,…

Probability · Mathematics 2014-09-12 Itai Gurvich

We investigate the long term behavior in terms of finite dimensional global and exponential attractors, as time goes to infinity, of solutions to a semilinear reaction-diffusion equation on non-smooth domains subject to nonlocal Robin…

Dynamical Systems · Mathematics 2016-07-20 Ciprian G. Gal , Mahamadi Warma

Dynamic wetting poses a well-known challenge in classical sharp-interface formulation as the no-slip wall condition leads to a contact line singularity that is typically regularized with a Navier boundary condition, often requiring…

Fluid Dynamics · Physics 2025-11-13 Tomas Fullana , Stéphane Zaleski , Gustav Amberg

Diffusion processes are fundamental in modelling stochastic dynamics in natural sciences. Recently, simulating such processes on complicated geometries has found applications for example in biology, where toroidal data arises naturally when…

Probability · Mathematics 2019-06-25 Mathias Højgaard Jensen , Anton Mallasto , Stefan Sommer

We consider the infinite horizon risk-sensitive problem for nondegenerate diffusions with a compact action space, and controlled through the drift. We only impose a structural assumption on the running cost function, namely…

Optimization and Control · Mathematics 2019-03-20 Ari Arapostathis , Anup Biswas

We consider a diffusion process in $\mathbb{R}^d$ with a generator of the form $ L:=\frac 12 e^{V(x)}div(e^{-V(x)}\nabla ) $ where $V$ is measurable and periodic. We only assume that $e^V$ and $e^{-V}$ are locally integrable. We then show…

Probability · Mathematics 2016-01-13 Moustapha Ba , Pierre Mathieu

We consider a class of infinite-dimensional diffusions where the interaction between the components is both spatial and temporal. We start the system from a Gibbs measure with finite-range uniformly bounded interaction. Under suitable…

Probability · Mathematics 2015-05-14 F. Redig , S. Roelly , W. Ruszel

We consider n-point sticky Brownian motions: a family of n diffusions that evolve as independent Brownian motions when they are apart, and interact locally so that the set of coincidence times has positive Lebesgue measure with positive…

Probability · Mathematics 2020-10-09 Guillaume Barraquand , Mark Rychnovsky

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