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This study in centered on models accounting for stochastic deformations of sample paths of random walks, embedded either in $\mathbb{Z}^2$ or in $\mathbb{Z}^3$. These models are immersed in multi-type particle systems with exclusion.…

Statistical Mechanics · Physics 2007-05-23 Guy Fayolle , Cyril Furtlehner

In this contribution we deal with the problem of learning an undirected graph which encodes the conditional dependence relationship between variables of a complex system, given a set of observations of this system. This is a very central…

Methodology · Statistics 2019-07-26 Daniela De Canditiis , Armando Guardasole

We present the path integral formulation of a broad class of generalized diffusion processes. Employing the path integral we derive exact expressions for the path probability densities and joint probability distributions for the class of…

Statistical Mechanics · Physics 2011-10-27 Rudolf Friedrich , Stephan Eule

A non-Grassmanian path integral representation is given for the solution of the Klein-Gordon and the Dirac equations. The trajectories of the path integral are rendered differentiable by the relativistic corrections. The nonrelativistic…

High Energy Physics - Theory · Physics 2009-10-30 Pierre Gosselin , Janos Polonyi

Methods for inference and simulation of linearly constrained Gaussian Markov Random Fields (GMRF) are computationally prohibitive when the number of constraints is large. In some cases, such as for intrinsic GMRFs, they may even be…

Methodology · Statistics 2021-06-04 David Bolin , Jonas Wallin

Contraction theory formulates the analysis of nonlinear systems in terms of Jacobian matrices. Although this provides the potential to develop a linear matrix inequality (LMI) framework for nonlinear control design, conditions are imposed…

Systems and Control · Electrical Eng. & Systems 2023-01-23 Yu Kawano , Kenji Kashima

In this manuscript, we consider the problem of learning a flow or diffusion-based generative model parametrized by a two-layer auto-encoder, trained with online stochastic gradient descent, on a high-dimensional target density with an…

Machine Learning · Computer Science 2025-11-11 Hugo Cui , Cengiz Pehlevan , Yue M. Lu

Continuous time random walks (CTRWs) are versatile models for anomalous diffusion processes that have found widespread application in the quantitative sciences. Their scaling limits are typically non-Markovian, and the computation of their…

Probability · Mathematics 2014-07-25 Mark M. Meerschaert , Peter Straka

We compute the Welschinger invariants of blowups of the projective plane at an arbitrary conjugation invariant configuration of points. Specifically, open analogues of the WDVV equation and Kontsevich-Manin axioms lead to a recursive…

Symplectic Geometry · Mathematics 2012-10-16 Asaf Horev , Jake P. Solomon

The relation between the restricted path integral approach to quantum measurement theory and the commonly accepted von Neumann wavefunction collapse postulate is presented. It is argued that in the limit of impulsive measurements the two…

Quantum Physics · Physics 2008-11-26 Tommaso Calarco

We introduce a notion of rough paths on embedded submanifolds and demonstrate that this class of rough paths is natural. On the way we develop a notion of rough integration and an efficient and intrinsic theory of rough differential…

Probability · Mathematics 2017-05-17 Thomas Cass , Bruce K. Driver , Christian Litterer

In this paper, a construction to imitate the Bernstein-Zelevinsky derivative for automorphic representations on $GL_n(\mathbb{A})$ is introduced. We will later consider the induced representation \[I(\tau_1,\tau_2;\underline{s}) =…

Representation Theory · Mathematics 2022-07-26 Zhuohui Zhang

This paper presents an efficient variational inference framework for deriving a family of structured gaussian process regression network (SGPRN) models. The key idea is to incorporate auxiliary inducing variables in latent functions and…

Machine Learning · Computer Science 2021-11-19 Rui Meng , Herbie Lee , Kristofer Bouchard

We study the gravitational collapse in modified gravitational theories. In particular, we analyze a general $f(R)$ model with uniformly collapsing cloud of self-gravitating dust particles. This analysis shares analogies with the formation…

General Relativity and Quantum Cosmology · Physics 2015-06-03 J. A. R. Cembranos , A. de la Cruz-Dombriz , B. Montes Nuñez

In this paper, I derive a generating function for discrete Motzkin paths of step size +2,+1,-1, restricted between two absorbing parallel lines, and generalized to arbitrary step weights. This continues off work of similar problems…

Combinatorics · Mathematics 2023-06-13 Cetin Hakimoglu-Brown

We consider a class of random self-similar fractals based on code trees which includes random recursive, homogeneous and V-variable fractals and many more. For such random fractals we consider mean values of the Lipschitz-Killing curvatures…

Probability · Mathematics 2025-05-09 Jan Rataj , Steffen Winter , Martina Zähle

We study the closed universe recollapse conjecture for positively curved Friedmann-Robertson-Walker (FRW) models in the Jordan frame of the second order gravity theory. We analyse the late time evolution of the model with the methods of the…

General Relativity and Quantum Cosmology · Physics 2007-05-23 John Miritzis

Graviweak theory seeks to unify gravity (specifically in its self-dual formulation) with the weak interaction, preying on their parallel chiral $SU(2)$ structures. In this paper we further this idea by folding it with the concept of…

High Energy Physics - Theory · Physics 2026-02-11 Stephon Alexander , Bruno Alexandre , Michael Fine , João Magueijo , Max Pezzelle

The path integral for Darcy's law with a stochastic conductivity, which characterizes flow through random porous media, is used as a basis for Wilson renormalization-group (RG) calculations in momentum space. A coarse graining procedure is…

Statistical Mechanics · Physics 2019-11-27 Umut C. Özer , Peter R. King , Dimitri D. Vvedensky

We perform a thorough analysis of the relationship between discrete and series representation path integral methods, which are the main numerical techniques used in connection with the Feynman-Kac formula. First, a new interpretation of the…

Statistical Mechanics · Physics 2009-11-07 Cristian Predescu , J. D. Doll