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Deep neural network ensembles combine the wisdom of multiple deep neural networks to improve the generalizability and robustness over individual networks. It has gained increasing popularity to study deep ensemble techniques in the deep…

Machine Learning · Computer Science 2023-11-20 Yanzhao Wu , Ka-Ho Chow , Wenqi Wei , Ling Liu

Moderate calibration, the expected event probability among observations with predicted probability z being equal to z, is a desired property of risk prediction models. Current graphical and numerical techniques for evaluating moderate…

Methodology · Statistics 2024-06-14 Mohsen Sadatsafavi , John Petkau

Consider a system of $N$ non-intersecting Brownian bridges in $[0,1]$, and let $\mathcal M_N(p)$ be the maximal height attained by the top path in the interval $[0,p]$, $p\in[0,1]$. It is known that, under a suitable rescaling, the…

Probability · Mathematics 2023-02-23 Yamit Yalanda , Nicolás Zalduendo

We provide a simple algorithm for construction of Brownian paths approximating those of a L\'evy process on a finite time interval. It requires knowledge of the L\'evy process trajectory on a chosen regular grid and the law of its endpoint,…

Probability · Mathematics 2021-10-25 Vladimir Fomichov , Jorge González Cázares , Jevgenijs Ivanovs

We construct and study curves with low H-constants on abelian and K3 surfaces. Using the Kummer $(16_{6})$-configurations on Jacobian surfaces and some $(16_{10})$-configurations of curves on $(1,3)$-polarized Abelian surfaces, we obtain…

Algebraic Geometry · Mathematics 2017-12-27 Xavier Roulleau

In this paper we revisit the one-dimensional tunneling problem. We consider Kemble's approximation for the transmission coefficient. We show how this approximation can be extended to above-barrier energies by performing the analytical…

Nuclear Theory · Physics 2017-03-22 A. J. Toubiana , L. F. Canto , M. S. Hussein

We propose several sampling architectures for the efficient acquisition of an ensemble of correlated signals. We show that without prior knowledge of the correlation structure, each of our architectures (under different sets of assumptions)…

Information Theory · Computer Science 2018-01-03 Ali Ahmed , Justin Romberg

Air-bridges play a critical role in the performance of microwave circuits integrated with superconducting quantum bits, and their mechanical stability is predominant for reliable operation. This study is devoted to the technological issues…

Green's canonical syzygy conjecture asserts a simple relationship between the Clifford index of a smooth projective curve and the shape of the minimal free resolution of its homogeneous ideal in the canonical embedding. We prove the…

Algebraic Geometry · Mathematics 2017-12-14 Anand Deopurkar

We study (slope-)stability properties of syzygy bundles on a projective space P^N given by ideal generators of a homogeneous primary ideal. In particular we give a combinatorial criterion for a monomial ideal to have a semistable syzygy…

Algebraic Geometry · Mathematics 2007-08-01 Holger Brenner

We consider a one-dimensional diffusion process with coefficients that are periodic outside of a finite 'interface region'. The question investigated in this article is the limiting long time / large scale behaviour of such a process under…

Probability · Mathematics 2010-05-14 Martin Hairer , Charles Manson

Bayesian simultaneous estimation of nonparametric quantile curves is a challenging problem, requiring a flexible and robust data model whilst satisfying the monotonicity or noncrossing constraints on the quantiles. This paper presents the…

Methodology · Statistics 2017-11-28 T. Rodrigues , J. -L. Dortet-Bernadet , Y. Fan

Recent experimental works on one-dimensional (1D) circular Kardar-Parisi-Zhang (KPZ) systems whose radii decrease in time have reported controversial conclusions about the statistics of their interfaces. Motivated by this, we investigate…

Statistical Mechanics · Physics 2018-07-25 Ismael S. S. Carrasco , Tiago J. Oliveira

We consider the one-dimensional Kardar-Parisi-Zhang (KPZ) equation with half Brownian motion initial condition, studied previously through the weakly asymmetric simple exclusion process. We employ the replica Bethe ansatz and show that the…

Statistical Mechanics · Physics 2012-06-15 Takashi Imamura , Tomohiro Sasamoto

In this paper we intend to give a comprehensive approach of functional inequalities for diffusion processes under some "curvature" assumptions. Our notion of curvature coincides with the usual $\Gamma_2$ curvature of Bakry and Emery in the…

Probability · Mathematics 2013-03-28 Patrick Cattiaux , Arnaud Guillin

We study the dynamics of overdamped Brownian particles interacting through soft pairwise potentials on a comb-like structure. Within the linearized Dean-Kawasaki framework, we characterize the particle density fluctuations by computing…

Statistical Mechanics · Physics 2025-05-21 Davide Venturelli , Pierre Illien , Aurélien Grabsch , Olivier Bénichou

I prove that every adapted Brownian bridge on a geodesically complete connected Riemannian manifold is a semimartingale including its terminal time, without any further assumptions on the geometry. In particular, it follows that every such…

Probability · Mathematics 2016-04-29 Batu Güneysu

The diffusion coefficient--a measure of dissipation, and the entropy--a measure of fluctuation are found to be intimately correlated in many physical systems. Unlike the fluctuation dissipation theorem in linear response theory, the…

Statistical Mechanics · Physics 2021-03-25 Yi Liao , Xiao-Bo Gong

Strong embeddings, that is, couplings between a partial sum process of a sequence of random variables and a Brownian motion, have found numerous applications in probability and statistics. We extend Chatterjee's novel use of Stein's method…

Probability · Mathematics 2016-12-15 Chinmoy Bhattacharjee , Larry Goldstein

Deep ensemble is a simple yet powerful way to improve the performance of deep neural networks. Under this motivation, recent works on mode connectivity have shown that parameters of ensembles are connected by low-loss subspaces, and one can…

Machine Learning · Computer Science 2023-06-21 EungGu Yun , Hyungi Lee , Giung Nam , Juho Lee
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