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In including random effects to account for dependent observations, the odds ratio interpretation of logistic regression coefficients is changed from population-averaged to subject-specific. This is unappealing in many applications,…

Methodology · Statistics 2025-12-04 Changwoo J. Lee , David B. Dunson

Symmetry principles underlie and guide scientific theory and research, from Curie's invariance formulation to modern applications across physics, chemistry, and mathematics. Building on a recent matrix Lie group measurement model, this…

Methodology · Statistics 2025-12-19 William R. Nugent

We obtain a representation of an inhomogeneous Levy process in a Lie group or a homogeneous space in terms of a drift, a matrix function and a measure function. Because the stochastic continuity is not assumed, our result generalizes the…

Probability · Mathematics 2014-12-30 Ming Liao

We propose a method for estimating first passage time densities of one-dimensional diffusions via Monte Carlo simulation. Our approach involves a representation of the first passage time density as expectation of a functional of the…

Probability · Mathematics 2010-08-10 Tomoyuki Ichiba , Constantinos Kardaras

For a fixed flow-based generative model under a small inference budget, sample quality can depend strongly on where the sampler spends its few function evaluations. Flow matching and Schr\"odinger bridges define probability paths, yet their…

Machine Learning · Computer Science 2026-05-18 Bruno Trentini , Dejan Stancevic , Michael M. Bronstein , Alexander Tong , Luca Ambrogioni

Computing sample means on Riemannian manifolds is typically computationally costly as exemplified by computation of the Fr\'echet mean which often requires finding minimizing geodesics to each data point for each step of an iterative…

Methodology · Statistics 2022-05-25 Mathias Højgaard Jensen , Stefan Sommer

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

Brownian simulations can be used to generate statistics relevant for studying molecular interactions or trafficking. However, the concurrent simulation of many Brownian trajectories at can become computationally intractable. Replacing…

Statistical Mechanics · Physics 2020-11-16 Ulrich Dobramysl , David Holcman

We derive explicit formulas for probabilities of Brownian motion with jumps crossing linear or piecewise linear boundaries in any finite interval. We then use these formulas to approximate the boundary crossing probabilities for general…

Probability · Mathematics 2012-05-16 Jinghai Shao , Liqun Wang

As an example for the fast calculation of distributional parameters of Gaussian processes, we propose a new Monte Carlo algorithm for the computation of quantiles of the supremum norm of weighted Brownian bridges. As it is known, the…

Computation · Statistics 2021-01-05 Jürgen Franke , Mario Hefter , André Herzwurm , Klaus Ritter , Stefanie Schwaar

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

Stochastic-gradient sampling methods are often used to perform Bayesian inference on neural networks. It has been observed that the methods in which notions of differential geometry are included tend to have better performances, with the…

Machine Learning · Computer Science 2024-04-02 Hanlin Yu , Marcelo Hartmann , Bernardo Williams , Arto Klami

We study the twirling semigroups of (super)operators, namely, certain quantum dynamical semigroups that are associated, in a natural way, with the pairs formed by a projective representation of a locally compact group and a convolution…

Quantum Physics · Physics 2014-11-20 P. Aniello , A. Kossakowski , G. Marmo , F. Ventriglia

We propose and test a method to interpolate sparsely sampled signals by a stochastic process with a broad range of spatial and/or temporal scales. To this end, we extend the notion of a fractional Brownian bridge, defined as fractional…

Data Analysis, Statistics and Probability · Physics 2021-01-05 J. Friedrich , S. Gallon , A. Pumir , R. Grauer

We present a collection of explicit diffusion approximations to small temperature Schr\"{o}dinger bridges on manifolds. Our most precise results are when both marginals are the same and the Schr\"{o}dinger bridge is on a manifold with a…

Probability · Mathematics 2025-12-23 Garrett Mulcahy , Soumik Pal

The goal of this paper is to define and study a notion of fractional Brownian motion on a Lie group. We define it as at the solution of a stochastic differential equation driven by a linear fractional Brownian motion. We show that this…

Probability · Mathematics 2007-05-23 F. Baudoin , L. Coutin

Instantaneous volatility of logarithmic return in the lognormal fractional SABR model is driven by the exponentiation of a correlated fractional Brownian motion. Due to the mixed nature of driving Brownian and fractional Brownian motions,…

Computational Finance · Quantitative Finance 2019-01-09 Jiro Akahori , Xiaoming Song , Tai-Ho Wang

From the classical theory of Lie algebras, it is well-known that the bilinear form $B(X,Y)={\rm tr}(XY)$ defines a non-degenerate scalar product on the simple Lie algebra ${\mathfrak{sl}}(n,{\mathbb R})$. Diagonalizing the Gram matrix $Gr$…

Differential Geometry · Mathematics 2024-10-22 Abraham Bobadilla Osses , Mauricio Godoy Molina

Barrier crossing is a widespread phenomenon across natural and engineering systems. While an abundant cross-disciplinary literature on the topic has emerged over the years, the stochastic underpinnings of the process are yet to be linked…

Statistical Mechanics · Physics 2024-12-19 Toby Kay , Luca Giuggioli

Starting from square-integrable wave functions on a Lie group, we build an invertible Fourier transform mapping them on wave functions on the dual of the Lie algebra. This is a group-theoretic version of the map from position space to…

Quantum Physics · Physics 2025-12-24 Mathieu Beauvillain , Blagoje Oblak , Marios Petropoulos