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The key distinguishing property of a Bayesian approach is marginalization, rather than using a single setting of weights. Bayesian marginalization can particularly improve the accuracy and calibration of modern deep neural networks, which…

Machine Learning · Computer Science 2022-03-31 Andrew Gordon Wilson , Pavel Izmailov

Double holography plays a crucial role in recent studies of Hawking radiation and information paradox by relating an intermediate picture, in which a dynamical gravity living on an end-of-the-world brane is coupled to a non-gravitational…

High Energy Physics - Theory · Physics 2022-08-10 Hidetoshi Omiya , Zixia Wei

Geospatial analysis is very much dominated by a Gaussian way of thinking, which assumes that things in the world can be characterized by a well-defined mean, i.e., things are more or less similar in size. However, this assumption is not…

Adaptation and Self-Organizing Systems · Physics 2015-02-23 Bin Jiang

In holographic duality, dynamics along the emergent extra-dimensional space describes a renormalization group (RG) flow of the corresponding quantum field theory (QFT). Following this idea, we develop an emergent holographic description of…

High Energy Physics - Theory · Physics 2022-04-27 Ki-Seok Kim , Shinsei Ryu , Kanghoon Lee

This paper presents a research study focused on uncovering the hidden population distribution from the viewpoint of a variational non-Bayesian approach. It asserts that if the hidden probability density function (PDF) has continuous partial…

Statistics Theory · Mathematics 2023-11-02 U Jin Choi , Kyung Soo Rim

The two surprising features of gravity are (a) the principle of equivalence and (b) the connection between gravity and thermodynamics. Using principle of equivalence and special relativity in the {\it local inertial frame}, one could obtain…

High Energy Physics - Theory · Physics 2009-11-07 T. Padmanabhan

We discuss the Hu-Washizu (HW) variational principle from a geometric standpoint. The mainstay of the present approach is to treat quantities defined on the co-tangent bundles of reference and deformed configurations as primal. Such a…

Mathematical Physics · Physics 2020-09-02 Bensingh Dhas , Debasish Roy

For (2+2)-dimensional nonholonomic distributions, the physical information contained into a spacetime (pseudo) Riemannian metric can be encoded equivalently into new types of geometric structures and linear connections constructed as…

General Relativity and Quantum Cosmology · Physics 2010-04-08 Sergiu I. Vacaru

In this paper, we study the geometric nonlinearity properties, such as curvature and torsion, in a dual coordinate system of the Riemannian manifold defined by the Gaussian distribution. We also give the Amari formulas explicitly in this…

Differential Geometry · Mathematics 2025-08-07 Prosper Rosaire Mama Assandje , Dongho Joseph , Thomas Bouetou Bouetou

We have previously discussed the characteristics of the gravitational waves (GW) and have, theoretically, shown that, like the corresponding electromagnetic (EM) waves, they also demonstrate, under certain conditions, holographic…

General Relativity and Quantum Cosmology · Physics 2008-11-26 D. Bar

In this work we explore many directions in the framework of gauge-gravity dualities. In type IIB theory we give an explicit derivation of the local metric for five branes wrapped on rigid two-cycles. Our derivation involves various…

High Energy Physics - Theory · Physics 2008-11-26 Keshav Dasgupta , Marc Grisaru , Rhiannon Gwyn , Sheldon Katz , Anke Knauf , Radu Tatar

Nonstationary Gaussian processes (GPs) are essential for modeling complex, locally heterogeneous spatial data. A common modeling approach is the spatial deformation method that warps the domain to recover isotropy. However, this static…

Machine Learning · Computer Science 2026-05-01 Minghao Gu , Weizhi Lin , Qiang Huang

Quantum fluctuations in spacetime can, in some cases, lead to distortion in astronomical images of faraway objects. In particular, a stochastic model of quantum gravity predicts an accumulated fluctuation in the path length $\Delta L$ with…

General Relativity and Quantum Cosmology · Physics 2024-05-24 Vincent S. H. Lee , Kathryn M. Zurek , Yanbei Chen

Determining if two histograms are consistent, whether they have been drawn from the same underlying distribution or not, is a common problem in physics. Existing approaches are not only limited in power but also inapplicable to histograms…

Data Analysis, Statistics and Probability · Physics 2010-09-29 M. J. Betancourt

Let $\bf{x}$ be a random variable with density $\rho(x)$ taking values in ${\mathbb R}^d$. We are interested in finding a representation for the shape of $\rho(x)$, i.e. for the orbit $\{ \rho(g\cdot x) | g\in E(d) \}$ of $\rho$ under the…

Probability · Mathematics 2021-11-23 Mireille Boutin , Kindyl King , Uli Walther

Data assimilation leads naturally to a Bayesian formulation in which the posterior probability distribution of the system state, given the observations, plays a central conceptual role. The aim of this paper is to use this Bayesian…

Data Analysis, Statistics and Probability · Physics 2013-01-01 K. J. H. Law , A. M. Stuart

The St\"uckelberg analysis of nonlinear massive gravity in the presence of a general fiducial metric is investigated. We develop a "covariant" formalism for the St\"uckelberg expansion by working with a local inertial frame, through which…

General Relativity and Quantum Cosmology · Physics 2015-01-26 Xian Gao , Tsutomu Kobayashi , Masahide Yamaguchi , Daisuke Yoshida

The notion of geometrical duality is discussed in the context of both Brans-Dicke theory and general relativity. It is shown that, in some particular solutions, the spacetime singularities that arise in usual Riemannian general relativity…

General Relativity and Quantum Cosmology · Physics 2009-10-31 Israel Quiros

A multivariate distribution can be described by a triangular transport map from the target distribution to a simple reference distribution. We propose Bayesian nonparametric inference on the transport map by modeling its components using…

Methodology · Statistics 2023-01-18 Matthias Katzfuss , Florian Schäfer

A Bayesian approach to variable selection which is based on the expected Kullback-Leibler divergence between the full model and its projection onto a submodel has recently been suggested in the literature. Here we extend this idea by…

Methodology · Statistics 2009-01-30 David Nott , Chenlei Leng