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The classical Okamura-Seymour theorem states that for an edge-capacitated, multi-commodity flow instance in which all terminals lie on a single face of a planar graph, there exists a feasible concurrent flow if and only if the cut…

Combinatorics · Mathematics 2015-06-18 James R. Lee , Manor Mendel , Mohammad Moharrami

Structurally stable (rough) flows on surfaces have only finitely many singularities and finitely many closed orbits, all of which are hyperbolic, and they have no trajectories joining saddle points. The violation of the last property leads…

Dynamical Systems · Mathematics 2017-06-07 Vladislav Kruglov , Dmitry Malyshev , Olga Pochinka

We propose a stochastic dynamics to be associated to a deterministic motion defined by a set of first order differential equation. The transitions that defined the stochastic dynamics are unidirectional and the rates are equal to the…

Statistical Mechanics · Physics 2024-11-13 Mário J. de Oliveira

Reservoir computing systems are constructed using a driven dynamical system in which external inputs can alter the evolving states of a system. These paradigms are used in information processing, machine learning, and computation. A…

Neural and Evolutionary Computing · Computer Science 2023-04-26 G Manjunath , Juan-Pablo Ortega

We develop a formalism to describe the formation of bound states in quantum field theory using an exact renormalization group flow equation. As a concrete example we investigate a nonrelativistic field theory with instantaneous interaction…

High Energy Physics - Theory · Physics 2010-10-04 S. Floerchinger

It is shown that a variety of deterministic cellular automaton models of highway traffic flow obey a variational principle which states that, for a given car density, the average car flow is a non-decreasing function of time. This result is…

Disordered Systems and Neural Networks · Physics 2016-12-21 Nino Boccara

We consider steady states of the incompressible Euler equation on two-dimensional domains. For non-radial analytic steady states on bounded simply connected domains, it was shown previously that there must be a global functional…

Analysis of PDEs · Mathematics 2026-05-12 Tarek M. Elgindi , Yupei Huang

Predicting future states or actions of a given system remains a fundamental, yet unsolved challenge of intelligence, especially in the scope of complex and non-deterministic scenarios, such as modeling behavior of humans. Existing…

Machine Learning · Computer Science 2020-12-01 Maciej Zięba , Marcin Przewięźlikowski , Marek Śmieja , Jacek Tabor , Tomasz Trzcinski , Przemysław Spurek

We study a general mass transport model on an arbitrary graph consisting of $L$ nodes each carrying a continuous mass. The graph also has a set of directed links between pairs of nodes through which a stochastic portion of mass, chosen from…

Statistical Mechanics · Physics 2007-05-23 M. R. Evans , Satya N. Majumdar , R. K. P. Zia

Conditions are presented for different types of identifiability of discrete variable models generated over an undirected graph in which one node represents a binary hidden variable. These models can be seen as extensions of the latent class…

Methodology · Statistics 2013-12-12 Elena Stanghellini , Barbara Vantaggi

A word-to-word function is rational if it can be realized by a non-deterministic one-way transducer. Over finite words, it is a classical result that any rational function is regular, i.e. it can be computed by a deterministic two-way…

Formal Languages and Automata Theory · Computer Science 2022-11-04 Olivier Carton , Gaëtan Douéneau-Tabot

Flow-based generative models have highly desirable properties like exact log-likelihood evaluation and exact latent-variable inference, however they are still in their infancy and have not received as much attention as alternative…

Computer Vision and Pattern Recognition · Computer Science 2020-04-06 Albert Pumarola , Stefan Popov , Francesc Moreno-Noguer , Vittorio Ferrari

Adding a column of numbers produces "carries" along the way. We show that random digits produce a pattern of carries with a neat probabilistic description: the carries form a one-dependent determinantal point process. This makes it easy to…

Probability · Mathematics 2009-04-24 Alexei Borodin , Persi Diaconis , Jason Fulman

Real-world scenarios demand reasoning about process, more than final outcome prediction, to discover latent causal chains and better understand complex systems. It requires the learning algorithms to offer both accurate predictions and…

Artificial Intelligence · Computer Science 2019-01-09 Xiaoran Xu , Songpeng Zu , Chengliang Gao , Yuan Zhang , Wei Feng

Constructal Law states that a finite-size flow system that persists in time evolves its configuration so as to provide progressively easier access to the currents that flow through it. Classical Constructal theory derives hierarchical flow…

Dynamical Systems · Mathematics 2026-03-10 Pascal Stiefenhofer

We present elements of a typing theory for flow networks, where "types", "typings", and "type inference" are formulated in terms of familiar notions from polyhedral analysis and convex optimization. Based on this typing theory, we develop…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-05-22 Assaf Kfoury

We consider open multi-class queueing networks with general arrival processes, general processing time sequences and Bernoulli routing. The network is assumed to be operating under an arbitrary work-conserving scheduling policy that makes…

Probability · Mathematics 2021-11-23 Sarat Babu Moka , Yoni Nazarathy , Werner Scheinhardt

Adapting Lindstr\"om's well-known construction, we consider a wide class of functions which are generated by flows in a planar acyclic directed graph whose vertices (or edges) take weights in an arbitrary commutative semiring. We give a…

Combinatorics · Mathematics 2012-01-31 Vladimir I. Danilov , Alexander V. Karzanov , Gleb A. Koshevoy

Determinism is established in quantum mechanics by tracing the probabilities in the Born rules back to the absolute (overall) phase constants of the wave functions and recognizing these phase constants as pseudorandom numbers. The reduction…

Quantum Physics · Physics 2019-07-25 Arthur Jabs

Fueled by the expressive power of deep neural networks, normalizing flows have achieved spectacular success in generative modeling, or learning to draw new samples from a distribution given a finite dataset of training samples. Normalizing…

Machine Learning · Computer Science 2023-05-05 Yuehaw Khoo , Michael Lindsey , Hongli Zhao