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We demonstrate that the update of weight matrices in learning algorithms can be described in the framework of Dyson Brownian motion, thereby inheriting many features of random matrix theory. We relate the level of stochasticity to the ratio…

Disordered Systems and Neural Networks · Physics 2025-01-10 Gert Aarts , Biagio Lucini , Chanju Park

We study strong approximation of $d$-dimensional stochastic differential equations (SDEs) with a discontinuous drift coefficient. More precisely, we essentially assume that the drift coefficient is piecewise Lipschitz continuous with an…

Numerical Analysis · Mathematics 2025-04-03 Thomas Müller-Gronbach , Christopher Rauhögger , Larisa Yaroslavtseva

SLE is a random growth process based on Loewner's equation with driving parameter a one-dimensional Brownian motion running with speed $\kappa$. This process is intimately connected with scaling limits of percolation clusters and with the…

Probability · Mathematics 2007-05-23 Steffen Rohde , Oded Schramm

We consider the additive martingale $W_t(\lambda)$ and the derivative martingale $\partial W_t(\lambda)$ for one-dimensional supercritical super-Brownian motions with general branching mechanism. In the critical case $\lambda=\lambda_0$, we…

Probability · Mathematics 2021-09-13 Haojie Hou , Yan-Xia Ren , Renming Song

We present a new training methodology for transformers using a multilevel, layer-parallel approach. Through a neural ODE formulation of transformers, our application of a multilevel parallel-in-time algorithm for the forward and…

Machine Learning · Computer Science 2026-01-27 Shuai Jiang , Marc Salvadó-Benasco , Eric C. Cyr , Alena Kopaničáková , Rolf Krause , Jacob B. Schroder

This paper introduces a randomized tamed Euler scheme tailored for L\'evy-driven stochastic differential equations (SDEs) with superlinear random coefficients and Carath\'eodory-type drift. Under assumptions that allow for time-irregular…

Numerical Analysis · Mathematics 2025-10-22 Sani Biswas , Joaquin Fontbona

Schramm-Loewner Evolution (SLE) is a stochastic process that helps classify critical statistical models using one real parameter $\kappa$. Numerical study of SLE often involves curves that start and end on the real axis. To reduce numerical…

Statistical Mechanics · Physics 2015-05-27 M. N. Najafi , S. Moghimi-Araghi , S. Rouhani

In this paper we study strong approximation of the solution of a scalar stochastic differential equation (SDE) at the final time in the case when the drift coefficient may have discontinuities in space. Recently it has been shown in…

Probability · Mathematics 2019-04-22 Thomas Müller-Gronbach , Larisa Yaroslavtseva

The probability that a point is to one side of a curve in Schramm-Loewner evolution (SLE) can be obtained alternatively using boundary conformal field theory (BCFT). We extend the BCFT approach to treat two curves, forming, for example, the…

Mathematical Physics · Physics 2007-05-23 Adam Gamsa , John Cardy

This paper proves joint convergence of the approximation error for several stochastic integrals with respect to local Brownian semimartingales, for nonequidistant and random grids. The conditions needed for convergence are that the Lebesgue…

Probability · Mathematics 2013-09-24 Carl Lindberg , Holger Rootzén

In this paper, we are concerned with convergence rate of Euler-Maruyama (EM) scheme for stochastic differential delay equations (SDDEs) of neutral type, where the neutral term, the drift term and the diffusion term are allowed to be of…

Probability · Mathematics 2016-03-23 Yanting Ji , Jianhai Bao , Chenggui Yuan

This work presents a converged framework of Machine-Learning Assisted Turbulence Modeling (MLATM). Our objective is to develop a turbulence model directly learning from high fidelity data (DNS/LES) with eddy-viscosity hypothesis induced.…

Fluid Dynamics · Physics 2019-07-09 Weishuo Liu , Jian Fang , Stefano Rolfo , Lipeng Lu

This paper investigates the rate of convergence for the central limit theorem of linear spectral statistic (LSS) associated with large-dimensional sample covariance matrices. We consider matrices of the form ${\mathbf…

Probability · Mathematics 2025-06-05 Jian Cui , Jiang Hu , Zhidong Bai , Guorong Hu

We consider SDEs with bounded and $\alpha$-H\"older continuous drift, with $\alpha \in (0,1)$, driven by multiplicative noise. We show that under sufficient conditions on the diffusion matrix, which guarantee the existence of a unique…

Probability · Mathematics 2022-06-28 Teodor Holland

The Schramm-Loewner evolution (SLE_\kappa) is a candidate for the scaling limit of random curves arising in two-dimensional critical phenomena. When \kappa < 8, an instance of SLE_\kappa is a random planar curve with almost sure Hausdorff…

Probability · Mathematics 2009-06-23 Gregory F. Lawler , Scott Sheffield

The Complex Langevin (CL) method sometimes shows convergence to the wrong limit, even though the Schwinger-Dyson Equations (SDE) are fulfilled. We analyze this problem in a more general context for the case of one complex variable. We prove…

Mathematical Physics · Physics 2018-12-17 Lorenzo Luis Salcedo , Erhard Seiler

This paper introduces a new approach to the study of rates of convergence for posterior distributions. It is a natural extension of a recent approach to the study of Bayesian consistency. In particular, we improve on current rates of…

Statistics Theory · Mathematics 2007-08-22 Stephen G. Walker , Antonio Lijoi , Igor Prünster

Eigenvalue correlations of random matrix ensembles as a function of an external perturbation are investigated vis the Dyson Brownian Motion Model in the situation where the level density has a hard edge singularity. By solving a linearized…

Condensed Matter · Physics 2009-10-22 Kasper Eriksen , Yang Chen

Following the approach outlined in [18], convergence to SLE6 of the Exploration Processes for the correlated bond-triangular type models studied in [7] is established. This puts the said models in the same universality class as the standard…

Mathematical Physics · Physics 2010-04-27 I. Binder , L. Chayes , H. K. Lei

We consider the following second-order stochastic differential equation on $\mathbb{R}^{2d}$: \begin{equation*} dX_t^m=Y_t^mdt, \quad mdY_t^m=b(X_t^m)dt+\sigma(X_t^m)dB_t-Y^m_tdt, \end{equation*} where $X^m_t$ and $Y^m_t$ represent the…

Probability · Mathematics 2026-02-03 Shiyu Liu , Wei Liu , Lihu Xu