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Diffusion Models (DMs), as a leading class of generative models, offer key advantages for reinforcement learning (RL), including multi-modal expressiveness, stable training, and trajectory-level planning. This survey delivers a…

Machine Learning · Computer Science 2025-10-15 Changfu Xu , Jianxiong Guo , Yuzhu Liang , Haiyang Huang , Haodong Zou , Xi Zheng , Shui Yu , Xiaowen Chu , Jiannong Cao , Tian Wang

Diffusion models, a powerful and universal generative AI technology, have achieved tremendous success in computer vision, audio, reinforcement learning, and computational biology. In these applications, diffusion models provide flexible…

Machine Learning · Computer Science 2024-04-12 Minshuo Chen , Song Mei , Jianqing Fan , Mengdi Wang

Attention mechanisms have become a foundational component in diffusion models, significantly influencing their capacity across a wide range of generative and discriminative tasks. This paper presents a comprehensive survey of attention…

Machine Learning · Computer Science 2025-04-08 Litao Hua , Fan Liu , Jie Su , Xingyu Miao , Zizhou Ouyang , Zeyu Wang , Runze Hu , Zhenyu Wen , Bing Zhai , Yang Long , Haoran Duan , Yuan Zhou

Reaction-diffusion equations are studied on bounded, time-periodic domains with zero Dirichlet boundary conditions. The long-time behaviour is shown to depend on the principal periodic eigenvalue of a transformed periodic-parabolic problem.…

Analysis of PDEs · Mathematics 2023-07-18 Jane Allwright

We study reaction-diffusion processes with concentration-dependent diffusivity. First, we determine the decay of the concentration in the single-species and two-species diffusion-controlled annihilation processes. We then consider two…

Statistical Mechanics · Physics 2013-05-30 P. L. Krapivsky

End-to-end deep learning improves breast cancer classification on diffusion-weighted MR images (DWI) using a convolutional neural network (CNN) architecture. A limitation of CNN as opposed to previous model-based approaches is the…

The growth of domains of stripes evolving from random initial conditions is studied in numerical simulations of models of systems far from equilibrium such as Rayleigh-Benard convection. The scaling of the size of the domains deduced from…

patt-sol · Physics 2009-10-28 M. C. Cross , D. I. Meiron

Learning a model of dynamics from high-dimensional images can be a core ingredient for success in many applications across different domains, especially in sequential decision making. However, currently prevailing methods based on…

Machine Learning · Computer Science 2019-11-05 Neha Das , Maximilian Karl , Philip Becker-Ehmck , Patrick van der Smagt

Concentrations of matter, such as galaxies and galactic clusters, originated as very small density fluctuations in the early universe. The existence of galaxy clusters and super-clusters suggests that a natural scale for the matter…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-18 Bruce N. Miller , Jean-Louis Rouet

It is a well known fact that subdiffusion equations in terms of fractional derivatives can be obtained from Continuous Time Random Walk (CTRW) models with long-tailed waiting time distributions. Over the last years various authors have…

Biological Physics · Physics 2010-06-15 S. B. Yuste , E. Abad , K. Lindenberg

Based on a recently proposed non-equilibrium mechanism for spatial pattern formation [cond-mat/0312366] we study how morphogenesis can be controlled by locally coupled discrete dynamical networks, similar to gene regulation networks of…

Molecular Networks · Quantitative Biology 2007-05-23 Thimo Rohlf , Stefan Bornholdt

We investigate the non-equilibrium properties of an N-component scalar field theory. The time evolution of the correlation functions for an arbitrary ensemble of initial conditions is described by an exact functional differential equation.…

High Energy Physics - Phenomenology · Physics 2016-09-06 Luis M. A. Bettencourt , Christof Wetterich

The propagations of diseases, behaviors and information in real systems are rarely independent of each other, but they are coevolving with strong interactions. To uncover the dynamical mechanisms, the evolving spatiotemporal patterns and…

Physics and Society · Physics 2019-10-02 Wei Wang , Quan-Hui Liu , Junhao Liang , Yanqing Hu , Tao Zhou

Continuum models for the spatial dynamics of growing cell populations have been widely used to investigate the mechanisms underpinning tissue development and tumour invasion. These models consist of nonlinear partial differential equations…

Tissues and Organs · Quantitative Biology 2019-07-15 Mark AJ Chaplain , Tommaso Lorenzi , Fiona R Macfarlane

Density dependence is important in the ecology and evolution of microbial and cancer cells. Typically, we can only measure net growth rates, but the underlying density-dependent mechanisms that give rise to the observed dynamics can…

Populations and Evolution · Quantitative Biology 2025-06-04 Linh Huynh , Jacob G. Scott , Peter J. Thomas

The most general nonuniform reaction-diffusion models on a one-dimensional lattice with boundaries, for which the time evolution equations of corre- lation functions are closed, are considered. A transfer matrix method is used to find the…

Statistical Mechanics · Physics 2010-04-09 Amir Aghamohammadi , Mohammad Khorrami

Conformal field theories with central charge $c\le1$ on random surfaces have been extensively studied in the past. Here, this discussion is extended from their equilibrium distribution to their critical dynamics. This is motivated by the…

High Energy Physics - Theory · Physics 2025-06-03 Christof Schmidhuber

The microscopic structure and movement of reaction fronts in reaction diffusion systems far from equilibrium are investigated. We show that some three-site interaction models exhibit exact diffusive shock measures, i.e. domains of different…

Statistical Mechanics · Physics 2009-11-10 Matthias Paessens , Gunter M. Schuetz

We give a comprehensive study of the analytic properties and long-time behavior of solutions of a reaction-diffusion system in a bounded domain in the case where the nonlinearity satisfies the standard monotonicity assumption. We pay the…

Analysis of PDEs · Mathematics 2020-06-11 Anna Kostianko , Chunyou Sun , Sergey Zelik

Humans continuously adapt their style and language to a variety of domains. However, a reliable definition of `domain' has eluded researchers thus far. Additionally, the notion of discrete domains stands in contrast to the multiplicity of…

Computation and Language · Computer Science 2016-10-31 Sebastian Ruder , Parsa Ghaffari , John G. Breslin