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Matching platforms, from ridesharing to food delivery to competitive gaming, face a fundamental operational dilemma: match agents immediately to minimize waiting costs, or delay to exploit the efficiency gains of thicker markets. Yet…

Optimization and Control · Mathematics 2026-01-30 Jie Liu , Hailun Zhang , Jiheng Zhang

We introduce a stochastic lattice gas model including two particle species and two parallel lanes. One lane with exclusion interaction and directed motion and the other lane without exclusion and unbiased diffusion, mimicking a micotubule…

Statistical Mechanics · Physics 2009-11-13 M. Ebbinghaus , L. Santen

This paper focuses on the study of the Filament Based Lamellipodium Model (FBLM) and the corresponding Finite Element Method (FEM) from a numerical point of view. We study fundamental numerical properties of the FEM and justify the further…

Cell Behavior · Quantitative Biology 2018-01-30 Nikolaos Sfakianakis , Aaron Brunk

Continuous diffusion and flow matching models could represent a powerful alternative to autoregressive approaches for language modelling (LM), as they unlock a host of advantages currently reserved for continuous modalities, including…

Machine Learning · Computer Science 2026-05-12 Oscar Davis , Anastasiia Filippova , Pierre Ablin , Victor Turrisi , Amitis Shidani , Marco Cuturi , Louis Béthune

In the theory of two-sided matching markets there are two well-known models: the marriage model (where no money is involved) and the assignment model (where payments are involved). Roth and Sotomayor (1990) asked for an explanation for the…

Combinatorics · Mathematics 2007-05-23 Kimmo Eriksson , Johan Karlander

The cohesive collective motion (flocking, swarming) of autonomous agents is ubiquitously observed and exploited in both natural and man-made settings, thus, minimal models for its description are essential. In a model with continuous space…

Statistical Mechanics · Physics 2015-01-12 Illes J. Farkas , Jeromos Kun , Yi Jin , Gaoqi He , Mingliang Xu

Flow Matching (FM) is a recent generative modelling technique: we aim to learn how to sample from distribution $\mathfrak{X}_1$ by flowing samples from some distribution $\mathfrak{X}_0$ that is easy to sample from. The key trick is that…

Differential Geometry · Mathematics 2025-10-24 Finn M. Sherry , Bart M. N. Smets

The purpose of this paper is to adapt the empirical characteristic function (ECF) method to stable, but possibly not inverse stable linear stochastic system driven by the increments of a Levy-process. A remarkable property of the ECF method…

Methodology · Statistics 2014-01-07 L. Gerencser , M. Manfay

This chapter provides a tutorial overview of first principles methods to describe the properties of matter at the ground state or equilibrium. It begins with a brief introduction to quantum and statistical mechanics for predicting the…

Computational Engineering, Finance, and Science · Computer Science 2020-10-14 Jianzhong Wu , Mengyang Gu

The method of distributions is developed for systems that are governed by hyperbolic conservation laws with stochastic forcing. The method yields a deterministic equation for the cumulative density distribution (CDF) of a system state,…

Computational Physics · Physics 2019-09-05 Rik J. L. Rutjens , Gustaaf B. Jacobs , Daniel M. Tartakovsky

Mean field equilibrium (MFE) has emerged as a computationally tractable solution concept for large dynamic games. However, computing MFE remains challenging due to nonlinearities and the absence of contraction properties, limiting its…

Theoretical Economics · Economics 2025-06-23 Bar Light

We consider stability concepts for random matchings where agents have preferences over objects and objects have priorities for the agents. When matchings are deterministic, the standard stability concept also captures the fairness property…

Computer Science and Game Theory · Computer Science 2017-07-06 Haris Aziz , Bettina Klaus

There are insights of chaotic properties in economic systems and data. To prove the existence of chaotic dynamics, the establishment of a deterministic model is mandatory. A global modelling tool (GPoM) is used to search for mathematical…

Chaotic Dynamics · Physics 2025-10-24 Alexandre Meneceur , Vincent Lignon , Martin Rosalie

Recent advancements in generative modeling, particularly diffusion models, have opened new directions for time series modeling, achieving state-of-the-art performance in forecasting and synthesis. However, the reliance of diffusion-based…

Machine Learning · Computer Science 2025-05-13 Marcel Kollovieh , Marten Lienen , David Lüdke , Leo Schwinn , Stephan Günnemann

We propose a model for evolutionary game dynamics with three strategies $A$, $B$ and $C$ in the framework of Moran process in finite populations. The model can be described as a stochastic process which can be numerically computed from a…

Physics and Society · Physics 2007-05-23 Jing Wang , Feng Fu , Long Wang , Guangming Xie

Continuous normalizing flows (CNFs) can model data distributions with expressive infinite-length architectures. But this modeling involves computationally expensive process of solving an ordinary differential equation (ODE) during maximum…

Machine Learning · Computer Science 2024-10-15 Denis Gudovskiy , Tomoyuki Okuno , Yohei Nakata

Jamming is a phenomenon shared by a wide variety of systems, such as granular materials, foams, and glasses in their high density regime. This has motivated the development of a theoretical framework capable of explaining many of their…

Statistical Mechanics · Physics 2021-06-24 Rafael Díaz Hernández Rojas , Giorgio Parisi , Federico Ricci-Tersenghi

We study the probability of fixation in a stochastic two-species competition model. By identifying a naturally occurring fast timescale, we derive an approximation to the associated backward Kolmogorov equation that allows us to obtain an…

Populations and Evolution · Quantitative Biology 2020-09-04 Glenn Young , Andrew Belmonte

A general class of dynamical systems which can be trained to operate in classification and generation modes are introduced. A procedure is proposed to plant asymptotic stationary attractors of the deterministic model. Optimizing the…

Disordered Systems and Neural Networks · Physics 2025-10-15 Stefano Gagliani , Feliciano Giuseppe Pacifico , Lorenzo Chicchi , Duccio Fanelli , Diego Febbe , Lorenzo Buffoni , Raffaele Marino

Trajectory prediction and generation are crucial for autonomous robots in dynamic environments. While prior research has typically focused on either prediction or generation, our approach unifies these tasks to provide a versatile framework…

Robotics · Computer Science 2024-11-08 Sean Ye , Matthew Gombolay
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