English
Related papers

Related papers: Dynkin's Isomorphism with Sign Structure

200 papers

We construct the string field Hamiltonian for $c=1-\frac{6}{m(m+1)}$ string theory in the temporal gauge. In order to do so, we first examine the Schwinger-Dyson equations of the matrix chain models and propose the continuum version of…

High Energy Physics - Theory · Physics 2009-10-28 M. Ikehara , N. Ishibashi , H. kawai , T. Mogami , R. Nakayama , N. Sasakura

Machine learning methods on graphs have proven useful in many applications due to their ability to handle generally structured data. The framework of Gaussian Markov Random Fields (GMRFs) provides a principled way to define Gaussian models…

Machine Learning · Statistics 2022-06-13 Joel Oskarsson , Per Sidén , Fredrik Lindsten

Graphical Markov models combine conditional independence constraints with graphical representations of stepwise data generating processes.The models started to be formulated about 40 years ago and vigorous development is ongoing.…

Methodology · Statistics 2015-10-12 Nanny Wermuth

We aim at an explicit characterization of the renormalized Hamiltonian after decimation transformation of a one-dimensional Ising-type Hamiltonian with a nearest-neighbor interaction and a magnetic field term. To facilitate a deeper…

Statistical Mechanics · Physics 2015-06-05 Mei Yin

We consider multi-dimensional Gaussian processes and give a new condition on the covariance, simple and sharp, for the existence of stochastic area(s). Gaussian rough paths are constructed with a variety of weak and strong approximation…

Probability · Mathematics 2007-07-04 Peter Friz , Nicolas Victoir

Consider time-homogeneous discrete-time Markov chains $X$, $Y$, and $Z$ on countable state spaces, considered as stochastic processes with specified initial distributions. Suppose for maps $f$ and $g$ that $(f(X_t))_{t \ge 0}$ and…

Probability · Mathematics 2026-04-21 Edward Crane , Alexander E. Holroyd , Erin Russell

The relational formalism based on geometrical clocks and Dirac observables in linearized canonical cosmological perturbation theory is used to introduce an efficient method to find evolution equations for gauge invariant variables. Our…

General Relativity and Quantum Cosmology · Physics 2019-04-16 Kristina Giesel , Parampreet Singh , David Winnekens

Using the covariant approach and conformal transformations, we present a gauge-invariant formalism for cosmological perturbations in generalized Einstein theories (GETs), including the Brans-Dicke theory, theories with a non-minimally…

Astrophysics · Physics 2010-11-01 Toshinari Hirai , Kei-ichi Maeda

Counting and sampling directed acyclic graphs from a Markov equivalence class are fundamental tasks in graphical causal analysis. In this paper we show that these tasks can be performed in polynomial time, solving a long-standing open…

Machine Learning · Computer Science 2023-08-22 Marcel Wienöbst , Max Bannach , Maciej Liśkiewicz

Multivariate time series analysis is becoming an integral part of data analysis pipelines. Understanding the individual time point connections between covariates as well as how these connections change in time is non-trivial. To this aim,…

Machine Learning · Statistics 2021-02-04 Federico Ciech , Veronica Tozzo

A theory of systems with long-range correlations based on the consideration of binary N-step Markov chains is developed. In our model, the conditional probability that the i-th symbol in the chain equals zero (or unity) is a linear function…

Data Analysis, Statistics and Probability · Physics 2007-05-23 O. V. Usatenko , V. A. Yampol'skii

The theory of cosmological perturbations is a well elaborated field. To deal with the diffeomorphism invariance of general relativity one generally introduces combinations of the metric and matter perturbations which are gauge invariant up…

General Relativity and Quantum Cosmology · Physics 2018-05-31 Kristina Giesel , Adrian Herzog

The standard coalescent is widely used in evolutionary biology and population genetics to model the ancestral history of a sample of molecular sequences as a rooted and ranked binary tree. In this paper, we present a representation of the…

Probability · Mathematics 2020-12-16 Mackenzie Simper , Julia A. Palacios

In the context of signed line graphs, this article introduces a modified inflation technique to study strong Gram congruence of non-negative (integral quadratic) unit forms, and uses it to show that weak and strong Gram congruence coincide…

Combinatorics · Mathematics 2023-06-22 Jesus Arturo Jimenez Gonzalez

Ancestral graphs can encode conditional independence relations that arise in directed acyclic graph (DAG) models with latent and selection variables. However, for any ancestral graph, there may be several other graphs to which it is Markov…

Statistics Theory · Mathematics 2009-08-26 R. Ayesha Ali , Thomas S. Richardson , Peter Spirtes

Starting from the concept of involution of field equations, a universal method is proposed for constructing consistent interactions between the fields. The method equally well applies to the Lagrangian and non-Lagrangian equations and it is…

High Energy Physics - Theory · Physics 2015-06-11 D. S. Kaparulin , S. L. Lyakhovich , A. A. Sharapov

An analysis is given of the structure of a general two-dimensional Toda field theory involving bosons and fermions which is defined in terms of a set of simple roots for a Lie superalgebra. It is shown that a simple root system for a…

High Energy Physics - Theory · Physics 2009-10-30 Jonathan M. Evans , Jens Ole Madsen

In this paper, we explore the recursive structure of Baikov representations for Feynman integrals. We demonstrate that the various Baikov representations for all sectors of an integral family can be organized in a tree-like structure. Using…

High Energy Physics - Phenomenology · Physics 2023-10-12 Xuhang Jiang , Li Lin Yang

Existing approaches to differentiable structure learning of directed acyclic graphs (DAGs) rely on strong identifiability assumptions in order to guarantee that global minimizers of the acyclicity-constrained optimization problem identifies…

Machine Learning · Statistics 2024-11-28 Chang Deng , Kevin Bello , Pradeep Ravikumar , Bryon Aragam

I illustrate the phenomenological application of Dyson-Schwinger equations to the calculation of meson properties observable at TJNAF. Particular emphasis is given to this framework's ability to unify long-range effects constrained by…

Nuclear Theory · Physics 2010-03-04 Craig Roberts