English
Related papers

Related papers: Autoencoder-assisted study of directed percolation…

200 papers

Autoencoders receive latent models of input data. It was shown in recent works that they also estimate probability density functions of the input. This fact makes using the Bayesian decision theory possible. If we obtain latent models of…

Computer Vision and Pattern Recognition · Computer Science 2018-11-07 Vasily Morzhakov

The distributed computing analysis of the accuracy of automodel solutions for the Green's function of a wide class of superdiffusive transport of perturbation on a uniform background is carried out. The approximate automodel solutions have…

Numerical Analysis · Computer Science 2018-01-11 Alexander B. Kukushkin , Vladislav S. Neverov , Petr A. Sdvizhenskii , Vladimir V. Voloshinov

This review article gives an overview of recent progress in the field of non-equilibrium phase transitions into absorbing states with long-range interactions. It focuses on two possible types of long-range interactions. The first one is to…

Statistical Mechanics · Physics 2007-12-05 Haye Hinrichsen

The method of approximate automodel solution for the Green's function of the time-dependent superdiffusive (nonlocal) transport equations (J. Phys. A: Math. Theor. 49 (2016) 255002) is extended to the case of a finite velocity of carriers.…

Statistical Mechanics · Physics 2019-09-04 A. B. Kukushkin , A. A. Kulichenko

Recent progress in open many-body quantum systems has highlighted the importance of the Markov length, the characteristic scale over which conditional correlations decay. It has been proposed that non-equilibrium phases of matter can be…

Statistical Mechanics · Physics 2026-01-09 Yu-Hsueh Chen , Tarun Grover

We consider a nonequilibrium process on a timeline with discrete sites which evolves by a non-Markovian update rule in such a way that an active site at time t activates one or several sites in the future at time t+dt. The time intervals dt…

Statistical Mechanics · Physics 2009-02-10 Andre C. Barato , Haye Hinrichsen

Autoencoders are powerful machine learning models used to compress information from multiple data sources. However, autoencoders, like all artificial neural networks, are often unidentifiable and uninterpretable. This research focuses on…

We present a machine-learning method for data-driven synchronization of rhythmic spatiotemporal patterns in reaction-diffusion systems. Based on the phase autoencoder [Yawata {\it et al.}, Chaos {\bf 34}, 063111 (2024)], we map…

Adaptation and Self-Organizing Systems · Physics 2026-01-06 Koichiro Yawata , Ryo Sakuma , Kai Fukami , Kunihiko Taira , Hiroya Nakao

Phase transitions from an active into an absorbing, inactive state are generically described by the critical exponents of directed percolation (DP), with upper critical dimension d_c = 4. In the framework of single-species…

Condensed Matter · Physics 2009-10-31 Y. Y. Goldschmidt , H. Hinrichsen , M. Howard , U. C. Täuber

In the near future, more and more machines will perform tasks in the vicinity of human spaces or support them directly in their spatially bound activities. In order to simplify the verbal communication and the interaction between robotic…

Machine Learning · Computer Science 2020-04-14 Sebastian Feld , Steffen Illium , Andreas Sedlmeier , Lenz Belzner

Imitation learning is an intuitive approach for teaching motion to robotic systems. Although previous studies have proposed various methods to model demonstrated movement primitives, one of the limitations of existing methods is that the…

Robotics · Computer Science 2020-09-24 Takayuki Osa , Shuhei Ikemoto

Distributions are fundamental statistical elements that play essential theoretical and practical roles. The article discusses experiences of training neural networks to classify univariate empirical distributions and to represent them on…

Machine Learning · Computer Science 2020-04-07 Alex Glushkovsky

Generative modeling frameworks have emerged as an effective approach to capture high-dimensional image distributions from large datasets without requiring domain-specific knowledge, a capability essential for longitudinal disease…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Ayantika Das , Arunima Sarkar , Keerthi Ram , Mohanasankar Sivaprakasam

We solve an adaptive search model where a random walker or L\'evy flight stochastically resets to previously visited sites on a $d$-dimensional lattice containing one trapping site. Due to reinforcement, a phase transition occurs when the…

Statistical Mechanics · Physics 2017-10-11 Andrea Falcón-Cortés , Denis Boyer , Luca Giuggioli , Satya N. Majumdar

We generalize the previous study on the application of variational autoencoders to the two-dimensional Ising model to a system with anisotropy. Due to the self-duality property of the system, the critical points can be located exactly for…

Disordered Systems and Neural Networks · Physics 2023-10-31 Anshumitra Baul , Nicholas Walker , Juana Moreno , Ka-Ming Tam

For centuries, scientists have observed nature to understand the laws that govern the physical world. The traditional process of turning observations into physical understanding is slow. Imperfect models are constructed and tested to…

Machine Learning · Computer Science 2023-01-27 M. Giselle Fernández-Godino , Donald D. Lucas , Qingkai Kong

The non-equilibrium phase transition in models for epidemic spreading with long-range infections in combination with incubation times is investigated by field-theoretical and numerical methods. Here the spreading process is modelled by…

Statistical Mechanics · Physics 2007-05-23 Julian Adamek , Michael Keller , Arne Senftleben , Haye Hinrichsen

We consider self-avoiding walk and percolation in $\Zd$, oriented percolation in $\Zd\times\Zp$, and the contact process in $\Zd$, with $p D(\cdot)$ being the coupling function whose range is denoted by $L<\infty$. For percolation, for…

Probability · Mathematics 2007-05-23 Remco van der Hofstad , Akira Sakai

This paper studies a stylized model of local interaction where agents choose from an ever increasing set of vertically ranked actions, e.g. technologies. The driving forces of the model are infrequent upward shifts (``updates''), followed…

Statistical Mechanics · Physics 2007-05-23 A. Arenas , A. Diaz-Guilera , C. J. Perez , F. Vega-Redondo

We introduce a model for directed percolation with a long-range temporal diffusion, while the spatial diffusion is kept short ranged. In an interpretation of directed percolation as an epidemic process, this non-Markovian modification can…

Statistical Mechanics · Physics 2009-11-11 Andrea Jimenez-Dalmaroni