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We consider the problem of discretizing evolution operators of linear delay equations with the aim of approximating their spectra, which is useful in investigating the stability properties of (nonlinear) equations via the principle of…

Numerical Analysis · Mathematics 2026-01-01 Alessia andò , Giusy Bosco , Dimitri Breda , Davide Liessi

We present an extension of the methods of classical Lie group analysis of differential equations to equations involving generalized functions (in particular: distributions). A suitable framework for such a generalization is provided by…

Functional Analysis · Mathematics 2007-05-23 Michael Kunzinger , Michael Oberguggenberger

Over the past 30 years many researchers in the field of evolutionary computation have put a lot of effort to introduce various approaches for solving hard problems. Most of these problems have been inspired by major industries so that…

Neural and Evolutionary Computing · Computer Science 2016-06-23 Mohammad Reza Bonyadi , Zbigniew Michalewicz , Frank Neumann , Markus Wagner

Simple analytic considerations are applied to recently discovered patterns in a generalized Fisher equation for population dynamics. The generalization consists of the inclusion of non-local competition interactions among individuals. We…

Pattern Formation and Solitons · Physics 2007-05-23 M. A. Fuentes , M. N. Kuperman , V. M. Kenkre

1) Micro-evolutionary predictions are complicated by ecological feedbacks like density dependence, while ecological predictions can be complicated by evolutionary change. A widely used approach in micro-evolution, quantitative genetics,…

Populations and Evolution · Quantitative Biology 2015-09-07 Tim Coulson , Floriane Plard , Susanne Schindler , Arpat Ozgul , Jean-Michel Gaillard

Diffusion models are a class of generative models that serve to establish a stochastic transport map between an empirically observed, yet unknown, target distribution and a known prior. Despite their remarkable success in real-world…

Machine Learning · Computer Science 2025-03-13 Puheng Li , Zhong Li , Huishuai Zhang , Jiang Bian

The invariant subspace method is refined to present more unity and more diversity of exact solutions to evolution equations. The key idea is to take subspaces of solutions to linear ordinary differential equations as invariant subspaces…

Exactly Solvable and Integrable Systems · Physics 2015-06-04 Wen-Xiu Ma

This paper aims to the conditions of traffic flow evolving to stability and the stability of equilibrium under demand time-varying of traffic networks. The general framework of the evolution of flow dynamics by adopting evolutionary game…

Physics and Society · Physics 2018-07-26 Xingguang Chen

We consider stochastic equations for the class of formal mappings. Existence and uniqueness of solution, as well as evolution property are proved.

funct-an · Mathematics 2008-02-03 I. Ya. Spectorsky

Advanced observational facilities allow to trace back the chemical evolution of the Universe, on the one hand, from local objects of different ages and, secondly, by direct observations of redshifted objects. The chemical enrichment serves…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-18 Gerhard Hensler , Simone Recchi

The modeling of probability distributions, specifically generative modeling and density estimation, has become an immensely popular subject in recent years by virtue of its outstanding performance on sophisticated data such as images and…

Machine Learning · Statistics 2023-01-02 Hongkang Yang

Multiple data types naturally co-occur when describing real-world phenomena and learning from them is a long-standing goal in machine learning research. However, existing self-supervised generative models approximating an ELBO are not able…

Machine Learning · Computer Science 2021-06-28 Thomas M. Sutter , Imant Daunhawer , Julia E. Vogt

Modeling structure and behavior of software systems plays a crucial role, in various areas of software engineering. As with other software engineering artifacts, software models are subject to evolution. Supporting modelers in evolving…

Software Engineering · Computer Science 2023-12-20 Christof Tinnes , Thomas Fuchß , Uwe Hohenstein , Sven Apel

Practical Bayesian learning often requires (1) online inference, (2) dynamic models, and (3) ensembling over multiple different models. Recent advances have shown how to use random feature approximations to achieve scalable, online…

Machine Learning · Computer Science 2024-05-03 Daniel Waxman , Petar M. Djurić

This book deals with the theory of generalized algebraic transformations, which is elaborated with the aim to provide a relatively simple theoretical tool that enables an exact treatment of diverse more complex lattice-statistical models.…

Statistical Mechanics · Physics 2010-08-13 Jozef Strecka

Multimodal learning leverages the integration of diverse data modalities to enhance performance in complex tasks. Yet, it frequently encounters incomplete or redundant modality data in real-world scenarios. This paper presents a…

Machine Learning · Computer Science 2026-05-05 Richeng Zhou , Xuelin Zhang , Liyuan Liu

Model explainability is crucial for human users to be able to interpret how a proposed classifier assigns labels to data based on its feature values. We study generalized linear models constructed using sets of feature value rules, which…

Machine Learning · Statistics 2023-11-06 Sanjeeb Dash , Soumyadip Ghosh , Joao Goncalves , Mark S. Squillante

In this note we introduce generalised pairs from the perspective of the evolution of the notion of space in birational algebraic geometry. We describe some applications of generalised pairs in recent years and then mention a few open…

Algebraic Geometry · Mathematics 2020-08-10 Caucher Birkar

With the rise of computers, simulation models have emerged beside the more traditional statistical and mathematical models as a third pillar for ecological analysis. Broadly speaking, a simulation model is an algorithm, typically…

Populations and Evolution · Quantitative Biology 2018-12-24 Florian Hartig

Mathematical models play an increasingly important role in the interpretation of biological experiments. Studies often present a model that generates the observations, connecting hypothesized process to an observed pattern. Such generative…

Populations and Evolution · Quantitative Biology 2014-06-18 Steven A. Frank