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Evolutionary branching is analysed in a stochastic, individual-based population model under mutation and selection. In such models, the common assumption is that individual reproduction and life career are characterised by values of a…

Populations and Evolution · Quantitative Biology 2025-10-01 S. Sagitov , B. Mehlig , P. Jagers , V. Vatutin

Evolutionary optimization algorithms are often derived from loose biological analogies and struggle to leverage information obtained during the sequential course of optimization. An alternative promising approach is to leverage data and…

Artificial Intelligence · Computer Science 2024-03-06 Robert Tjarko Lange , Yingtao Tian , Yujin Tang

In this paper we examine the concept of complexity as it applies to generative and evolutionary art and design. Complexity has many different, discipline specific definitions, such as complexity in physical systems (entropy), algorithmic…

Neural and Evolutionary Computing · Computer Science 2022-01-06 Jon McCormack , Camilo Cruz Gambardella

Latent diffusers revolutionized the generative AI and inspired creative art. When denoising the latent, the predicted original image at each step collectively animates the formation. However, the animation is limited by the denoising nature…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Shih-Chieh Su

Face attributes are interesting due to their detailed description of human faces. Unlike prior researches working on attribute prediction, we address an inverse and more challenging problem called face attribute manipulation which aims at…

Computer Vision and Pattern Recognition · Computer Science 2017-04-13 Wei Shen , Rujie Liu

Generative models have enabled intuitive image creation and manipulation using natural language. In particular, diffusion models have recently shown remarkable results for natural image editing. In this work, we propose to apply diffusion…

Vector graphics, known for their scalability and user-friendliness, provide a unique approach to visual content compared to traditional pixel-based images. Animation of these graphics, driven by the motion of their elements, offers enhanced…

Computer Vision and Pattern Recognition · Computer Science 2025-09-10 Wenshuo Gao , Xicheng Lan , Luyao Zhang , Shuai Yang

Creating a stroke-by-stroke evolution process of a visual artwork tries to bridge the emotional and educational gap between the finished static artwork and its creation process. Recent stroke-based painting systems focus on capturing stroke…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Jeripothula Prudviraj , Vikram Jamwal

Evolutionary algorithms (EAs) are population-based metaheuristics, originally inspired by aspects of natural evolution. Modern varieties incorporate a broad mixture of search mechanisms, and tend to blend inspiration from nature with…

Neural and Evolutionary Computing · Computer Science 2018-05-29 David W. Corne , Michael A. Lones

Diversity is an important factor in evolutionary algorithms to prevent premature convergence towards a single local optimum. In order to maintain diversity throughout the process of evolution, various means exist in literature. We analyze…

Neural and Evolutionary Computing · Computer Science 2018-10-31 Thomas Gabor , Lenz Belzner , Claudia Linnhoff-Popien

Typefaces are an essential resource employed by graphic designers. The increasing demand for innovative type design work increases the need for good technological means to assist the designer in the creation of a typeface. We present an…

Neural and Evolutionary Computing · Computer Science 2018-06-27 Tiago Martins , João Correia , Ernesto Costa , Penousal Machado

Directed graphs are widely used to model data flow and execution dependencies in streaming applications. This enables the utilization of graph partitioning algorithms for the problem of parallelizing computation for multiprocessor…

Data Structures and Algorithms · Computer Science 2017-09-26 Orlando Moreira , Merten Popp , Christian Schulz

Diversity plays a crucial role in evolutionary computation. While diversity has been mainly used to prevent the population of an evolutionary algorithm from premature convergence, the use of evolutionary algorithms to obtain a diverse set…

Neural and Evolutionary Computing · Computer Science 2018-02-16 Aneta Neumann , Wanru Gao , Carola Doerr , Frank Neumann , Markus Wagner

Nowadays, image-to-image translation methods, are the state of the art for the enhancement of natural images. Even if they usually show high performance in terms of accuracy, they often suffer from several limitations such as the generation…

Computer Vision and Pattern Recognition · Computer Science 2022-07-15 Marco Cotogni , Claudio Cusano

Edges are a basic and fundamental feature in image processing, that are used directly or indirectly in huge amount of applications. Inspired by the expansion of image resolution and processing power dilated convolution techniques appeared.…

Computer Vision and Pattern Recognition · Computer Science 2021-11-17 Ciprian Orhei , Victor Bogdan , Cosmin Bonchis

We describe several techniques for using bulk matter for special purpose computation. In each case it is necessary to use an evolutionary algorithm to program the substrate on which the computation is to take place. In addition, the…

Other Condensed Matter · Physics 2007-05-23 Simon L. Harding , Julian F. Miller , Edward A. Rietman

Computational imaging has been playing a vital role in the development of natural sciences. Advances in sensory, information, and computer technologies have further extended the scope of influence of imaging, making digital images an…

Image and Video Processing · Electrical Eng. & Systems 2022-02-25 Bin Dong

The matching of the soundtrack in a movie or a video can have an enormous influence in the message being conveyed and its impact, in the sense of involvement and engagement, and ultimately in their aesthetic and entertainment qualities. Art…

Multimedia · Computer Science 2013-04-10 Jorge Gomes , Fernando Silva , Teresa Chambel

We provide a novel approach to construct generative models for graphs. Instead of using the traditional probabilistic models or deep generative models, we propose to instead find an algorithm that generates the data. We achieve this using…

Machine Learning · Computer Science 2023-04-26 Mihai Babiac , Karolis Martinkus , Roger Wattenhofer

In this paper, we wish to investigate the dynamics of information transfer in evolutionary dynamics. We use information theoretic tools to track how much information an evolving population has obtained and managed to retain about different…

Populations and Evolution · Quantitative Biology 2021-04-09 Nicholas Guttenberg
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