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We present a Bayesian model selection approach to estimate the intrinsic dimensionality of a high-dimensional dataset. To this end, we introduce a novel formulation of the probabilisitic principal component analysis model based on a…

Methodology · Statistics 2019-05-22 Charles Bouveyron , Pierre Latouche , Pierre-Alexandre Mattei

This thesis studies matrix field theories, which are a special type of matrix models. First, the different types of applications are pointed out, from (noncommutative) quantum field theory over 2-dimensional quantum gravity up to algebraic…

Mathematical Physics · Physics 2020-05-18 Alexander Hock

Similarly to the complex matrix model, the rainbow tensor models are superintegrable in the sense that arbitrary Gaussian correlators are explicitly expressed through the Clebsh-Gordan coefficients. We introduce associated (Ooguri-Vafa…

High Energy Physics - Theory · Physics 2020-01-27 H. Itoyama , A. Mironov , A. Morozov

In a complete metric space that is equipped with a doubling measure and supports a Poincar\'e inequality, we study strict subsets, i.e. sets whose variational capacity with respect to a larger reference set is finite, in the case $p=1$.…

Metric Geometry · Mathematics 2019-03-12 Panu Lahti

Since the ($\beta$-deformed) hermitian one-matrix models can be represented as the integrated conformal field theory (CFT) expectation values, we construct the operators in terms of the generators of the Heisenberg algebra such that the…

High Energy Physics - Theory · Physics 2022-10-26 Rui Wang , Chun-Hong Zhang , Fu-Hao Zhang , Wei-Zhong Zhao

A widely used approach to compute the action $f(A)v$ of a matrix function $f(A)$ on a vector $v$ is to use a rational approximation $r$ for $f$ and compute $r(A)v$ instead. If $r$ is not computed adaptively as in rational Krylov methods,…

Numerical Analysis · Mathematics 2021-09-09 Andreas Frommer , Karsten Kahl , Manuel Tsolakis

In this paper, we first review one of difficult parts of the proof of Witten's conjecture by Kontsevich that had not been emphasized before. In the derivation of the KdV equations, we review the boson-fermion correspondence method \cite{K}…

Mathematical Physics · Physics 2009-05-28 Da Xu , Palle Jorgensen

We study expansions of a vector space $V$ over a field $\mathbb F$, possibly with extra structure, with a generic submodule over a subring of $\mathbb F$. We construct a natural expansion by existentially defined functions so that the…

Logic · Mathematics 2023-09-13 Alexander Berenstein , Christian d'Elbée , Evgueni Vassiliev

The Granular Instrumental Variables (GIV) methodology exploits panels with factor error structures to construct instruments to estimate structural time series models with endogeneity even after controlling for latent factors. We extend the…

Econometrics · Economics 2023-09-26 Saman Banafti , Tae-Hwy Lee

We study two-dimensional conformal field theories (CFTs) with boundaries via the conformal bootstrap. We derive a positive semi-definite program from crossing symmetry of three observables: the annulus partition function, the two-point…

High Energy Physics - Theory · Physics 2025-06-24 Marco Meineri , Bharathkumar Radhakrishnan

This paper concerns preprojective representations of a finite connected valued quiver without oriented cycles. For each such representation, an explicit formula in terms of the geometry of the quiver gives a unique, up to a certain…

Representation Theory · Mathematics 2007-05-23 Mark Kleiner , Helene R. Tyler

A general theory of vector-valued modular functions, holomorphic in the upper half-plane, is presented for finite dimensional representations of the modular group. This also provides a description of vector-valued modular forms of arbitrary…

Number Theory · Mathematics 2007-05-23 P. Bantay , T. Gannon

Variational autoencoders (VAE) often use Gaussian or category distribution to model the inference process. This puts a limit on variational learning because this simplified assumption does not match the true posterior distribution, which is…

Machine Learning · Computer Science 2017-02-28 Ke Sun , Xiangliang Zhang

We prove combinatorially the explicit relation between genus filtrated $s$-loop means of the Gaussian matrix model and terms of the genus expansion of the Kontsevich--Penner matrix model (KPMM). The latter is the generating function for…

High Energy Physics - Theory · Physics 2015-01-26 Jørgen Ellegaard Andersen , Leonid O. Chekhov , Paul Norbury , Robert C. Penner

We construct a generalized linear sigma model as an effective field theory (EFT) to describe nearly conformal gauge theories at low energies. The work is motivated by recent lattice studies of gauge theories near the conformal window, which…

We consider diagonal matrix elements of local operators between multi-soliton states in finite volume in the sine-Gordon model, and formulate a conjecture regarding their finite size dependence which is valid up to corrections exponential…

High Energy Physics - Theory · Physics 2013-03-14 T. Pálmai , G. Takács

Cahill-Glauber C(s)-correspondence is employed to construct Quasi-Probability Distribution Functions (QPDFs) for optical-polarization in phase space following equivalent description of polarization in Classical Optics. The proposed scheme…

Quantum Physics · Physics 2012-11-05 Ravi S. Singh , Sunil P. Singh , Gyaneshwar K. Gupta

In this paper, the nonlinear Volterra series expansion is extended and used to describe certain types of nonautonomous differential equations related to the inverse scattering problem in nuclear physics. The nonautonomous Volterra series…

Nuclear Theory · Physics 2024-11-14 Gabor Balassa

We employ the method used by Barbashov and collaborators in Quantum Field Theory to derive a path-integral representation of the $T$-matrix in nonrelativistic potential scattering which is free of functional integration over fictitious…

Nuclear Theory · Physics 2015-05-28 J. Carron , R. Rosenfelder

Gaussian Processes (GPs) are widely used to model dependencies in spatial statistics and machine learning. However, exact inference is computationally intractable for GP regression, with a time complexity of $O(n^3)$. The Vecchia…

Statistics Theory · Mathematics 2026-03-12 Botond Szabo , Yichen Zhu