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Large loss spikes in stochastic gradient descent are studied through a rigorous large-deviations analysis for a shallow, fully connected network in the NTK scaling. In contrast to full-batch gradient descent, the catapult phase is shown to…

Machine Learning · Computer Science 2026-04-14 Benjamin Gess , Daniel Heydecker

What is the path associated with the fastest Brownian particle that reaches a narrow window located on the boundary of a domain? Although the distribution of the fastest arrival times has been well studied in dimension 1, much less is known…

Statistical Mechanics · Physics 2018-05-01 Kanishka Basnayake , Akim Hubl , Zeev Schuss , David Holcman

The goal of the paper is to analytically examine escape probabilities for dynamical systems driven by symmetric $\alpha$-stable L\'evy motions. Since escape probabilities are solutions of a type of integro-differential equations (i.e.,…

Probability · Mathematics 2014-02-18 Huijie Qiao , Jinqiao Duan

We consider n-dimensional deterministic flows obtained by perturbing a gradient flow. We assume that the gradient flow admits a stable curve of stationary points, and thus if the perturbation is not too large the perturbed flow also admits…

Probability · Mathematics 2013-07-05 Christophe Poquet

We study the mean escape time in a market model with stochastic volatility. The process followed by the volatility is the Cox Ingersoll and Ross process which is widely used to model stock price fluctuations. The market model can be…

Statistical Mechanics · Physics 2009-11-11 Giovanni Bonanno , Davide Valenti , Bernardo Spagnolo

In this paper we study the reachability problem for discrete-time nonlinear stochastic systems. Our goal is to present a unified framework for calculating the probabilistic reachable set of discrete-time systems in the presence of both…

Systems and Control · Electrical Eng. & Systems 2024-09-17 Zishun Liu , Saber Jafarpour , Yongxin Chen

Periodic orbit theory is an effective tool for the analysis of classical and quantum chaotic systems. In this paper we extend this approach to stochastic systems, in particular to mappings with additive noise. The theory is cast in the…

chao-dyn · Physics 2009-10-31 Predrag Cvitanovic' , C. P. Dettmann , Ronnie Mainieri , Gabor Vattay

This work is devoted to the investigation of the most probable transition path for stochastic dynamical systems driven by either symmetric $\alpha$-stable L\'{e}vy motion ($0<\alpha<1$) or Brownian motion. For stochastic dynamical systems…

Dynamical Systems · Mathematics 2019-04-09 Yuanfei Huang , Ying Chao , Shenglan Yuan , Jinqiao Duan

Two classes of methods have been proposed for escaping from saddle points with one using the second-order information carried by the Hessian and the other adding the noise into the first-order information. The existing analysis for…

Optimization and Control · Mathematics 2018-03-05 Yi Xu , Rong Jin , Tianbao Yang

It is a common phenomenon in nature and technology that a system under perturbations exits a regime of its usual dynamics. Often it is possible to define a potential function whereby a potential well can be associated with a usual or…

Statistical Mechanics · Physics 2018-08-22 Tamás Bódai

Landscape is one of the key notions in literature on biological processes and physics of complex systems with both deterministic and stochastic dynamics. The large deviation theory (LDT) provides a possible mathematical basis for the…

Mathematical Physics · Physics 2012-06-19 Hao Ge , Hong Qian

We introduce a variational method for analyzing limit cycle oscillators in $\mathbb{R}^d$ driven by Gaussian noise. This allows us to derive exact stochastic differential equations (SDEs) for the amplitude and phase of the solution, which…

Probability · Mathematics 2017-11-03 Paul Bressloff , James MacLaurin

We investigate the maximum caliber variational principle as an inference algorithm used to predict dynamical properties of complex nonequilibrium, stationary, statistical systems in the presence of incomplete information. Specifically, we…

Statistical Mechanics · Physics 2016-12-28 Carlo Cafaro , Sean Alan Ali

We introduce a novel optimal transport framework for probabilistic circuits (PCs). While it has been shown recently that divergences between distributions represented as certain classes of PCs can be computed tractably, to the best of our…

Artificial Intelligence · Computer Science 2025-10-16 Adrian Ciotinga , YooJung Choi

We consider the overdamped limit of two-dimensional double well systems perturbed by weak noise. In the weak noise limit the most probable fluctuational path leading from either point attractor to the separatrix (the most probable escape…

Condensed Matter · Physics 2009-10-28 Robert S. Maier , Daniel L. Stein

We investigate the most probable phase portrait (MPPP) of a stochastic single-species model with the Allee effect using the non-local Fokker-Planck equation. This stochastic model is driven by non-Gaussian as well as Gaussian noise, and it…

Dynamical Systems · Mathematics 2023-02-03 Almaz Tesfay , Shenglan Yuan , Daniel Tesfay , James Brannan

We consider the rates of noise-induced switching between the stable states of dissipative dynamical systems with delay and also the rates of noise-induced extinction, where such systems model population dynamics. We study a class of systems…

Statistical Mechanics · Physics 2015-01-27 Ira B. Schwartz , Lora Billings , Thomas W. Carr , Mark Dykman

The escape mechanism of the four hill potential is explored. A thorough numerical investigation takes place in several types of two-dimensional planes and also in a three-dimensional subspace of the entire four-dimensional phase space in…

Chaotic Dynamics · Physics 2017-09-28 Euaggelos E. Zotos

Atypically large fluctuations in macroscopic non-equilibrium systems continue to attract interest. Their probability can often be determined by the optimal fluctuation method (OFM). The OFM brings about a conditional variational problem,…

Statistical Mechanics · Physics 2020-01-01 Alexander K. Hartmann , Baruch Meerson , Pavel Sasorov

This paper addresses the design and analysis of a multivariable gradient-based stochastic extremum-seeking control method for multi-input systems with arbitrary input delays. The approach accommodates systems with distinct time delays…

Optimization and Control · Mathematics 2024-11-19 Paulo Cesar Souza Silva , Paulo Cesar Pellanda , Tiago Roux Oliveira
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