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Explaining predictions based on multivariate time series data carries the additional difficulty of handling not only multiple features, but also time dependencies. It matters not only what happened, but also when, and the same feature could…

Machine Learning · Computer Science 2023-05-31 Joseph Enguehard

We investigate cosmological structure formation seeded by topological defects which may form during a phase transition in the early universe. First we derive a partially new, local and gauge invariant system of perturbation equations to…

Astrophysics · Physics 2009-10-28 R. Durrer , Z. -H. Zhou

We consider the dynamics of pattern formation in a system of point defects under sustained irradiation within the framework of the rate theory. In our study we generalize the standard approach taking into account a production of defects by…

Materials Science · Physics 2013-09-25 V. O. Kharchenko , D. O. Kharchenko

This paper describes how parametric resonances associated with a galactic potential subjected to relatively low amplitude, strictly periodic time-dependent perturbations can be impacted by pseudo-random variations in the pulsation…

Astrophysics · Physics 2009-11-10 Ioannis V. Sideris , Henry E. Kandrup

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are…

Populations and Evolution · Quantitative Biology 2018-07-19 George W. A. Constable , Alan J. McKane

The impact of gradient noise on training deep models is widely acknowledged but not well understood. In this context, we study the distribution of gradients during training. We introduce a method, Gradient Clustering, to minimize the…

Machine Learning · Computer Science 2020-07-10 Fartash Faghri , David Duvenaud , David J. Fleet , Jimmy Ba

Generative diffusion models have emerged as leading models in speech and image generation. However, in order to perform well with a small number of denoising steps, a costly tuning of the set of noise parameters is needed. In this work, we…

Machine Learning · Computer Science 2021-09-14 Robin San-Roman , Eliya Nachmani , Lior Wolf

High-dimensional data must be highly structured to be learnable. Although the compositional and hierarchical nature of data is often put forward to explain learnability, quantitative measurements establishing these properties are scarce.…

Machine Learning · Statistics 2025-03-04 Antonio Sclocchi , Alessandro Favero , Noam Itzhak Levi , Matthieu Wyart

The diffusion-driven Turing instability is a potential mechanism for spatial pattern formation in numerous biological and chemical systems. However, engineering these patterns and demonstrating that they are produced by this mechanism is…

Biological Physics · Physics 2025-12-02 Antonio Matas-Gil , Robert G. Endres

The development of data-driven heart sound classification models has been an active area of research in recent years. To develop such data-driven models in the first place, heart sound signals need to be captured using a signal acquisition…

Audio and Speech Processing · Electrical Eng. & Systems 2022-11-15 Davoud Shariat Panah , Andrew Hines , Susan McKeever

Noisy fluctuations are ubiquitous in complex systems. They play a crucial or delicate role in the dynamical evolution of gene regulation, signal transduction, biochemical reactions, among other systems. Therefore, it is essential to…

Dynamical Systems · Mathematics 2018-11-05 Jinqiao Duan , Hui Wang

The influence of external fluctuations in phase separation processes is analysed. These fluctuations arise from random variations of an external control parameter. A linear stability analysis of the homogeneous state shows that phase…

Condensed Matter · Physics 2009-10-30 J. Garcia-Ojalvo , A. M. Lacasta , J. M. Sancho , R. Toral

This article studies typical dynamics and fluctuations for a slow-fast dynamical system perturbed by a small fractional Brownian noise. Based on an ergodic theorem with explicit rates of convergence, which may be of independent interest, we…

Probability · Mathematics 2020-08-20 Solesne Bourguin , Siragan Gailus , Konstantinos Spiliopoulos

We review recent developments of slow/fast stochastic differential equations, and also present a new result on Diffusion Homogenisation Theory with fractional and non-strong-mixing noise and providing new examples. The emphasise of the…

Probability · Mathematics 2023-03-07 Johann Gehringer , Xue-Mei Li

In this paper we study the generation of primordial perturbation with a modified dispersion relation in various cosmological evolutions. We stress that the formation of the power spectrum is strongly dependent on the background. Working in…

Cosmology and Nongalactic Astrophysics · Physics 2009-09-01 Yi-Fu Cai , Xinmin Zhang

Diffusion models have recently emerged as powerful generative frameworks for producing high-quality images. A pivotal component of these models is the noise schedule, which governs the rate of noise injection during the diffusion process.…

Machine Learning · Computer Science 2025-02-10 Zhehao Guo , Jiedong Lang , Shuyu Huang , Yunfei Gao , Xintong Ding

The dynamics of a weakly dissipative Hamiltonian system submitted to stochastic perturbations has been investigated by means of asymptotic methods. The probability of noise-induced separatrix crossing, which drastically changes the fate of…

Classical Physics · Physics 2019-05-01 Jean-Régis Angilella

Growth-induced pattern formations in curved film-substrate structures have attracted extensive attentions recently. In most existing literature, the growth tensor is assumed to be homogeneous or piecewise homogeneous. In this paper, we aim…

Pattern Formation and Solitons · Physics 2021-11-10 Rui-Cheng Liu , Yang Liu , Zongxi Cai

We study the homology of simplicial complexes built via deterministic rules from a random set of vertices. In particular, we show that, depending on the randomness that generates the vertices, the homology of these complexes can either…

Probability · Mathematics 2013-01-09 Robert J. Adler , Omer Bobrowski , Shmuel Weinberger

Front dynamics modeled by a reaction-diffusion equation are studied under the influence of spatio-temporal structured noises. An effective deterministic model is analytical derived where the noise parameters, intensity, correlation time and…

Statistical Mechanics · Physics 2009-11-07 Miguel A. Santos , J. M. Sancho