Generative AI Algorithms and Their Applications to Real-World Problems
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".
Deadline for manuscript submissions: 20 October 2024 | Viewed by 1389
Special Issue Editors
Interests: machine learning; artificial intelligence
Interests: statistical and machine learning methods, with focus on modelling large-scale; highly structured and/or relational data (multivariate time series, graphs, networks, etc.); drug development; bioinformatics; healthcare
Special Issue Information
Dear Colleagues,
We invite you to submit your latest research in the area of generative modelling to this Special Issue “Generative AI Algorithms and Their Applications to Real-World Problems”.
Generative AI algorithms learn the underlying distribution of a given dataset, which allows them to generate new data samples that are similar to the original data distribution or create meaningful representations that capture the essential features of the data.
Generative AI algorithms are widely used for data representation and visualisation tasks. They can learn compact and meaningful representations of high-dimensional data, which can be visualised in lower-dimensional spaces. Notable generative models specifically used for data representation and visualisation include autoencoders and Generative Topographic Mapping (GTM). Some generative algorithms used for generating new data include Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Autoregressive Models.
Generative AI algorithms have found a wide range of applications in various real-world problems across different domains such as text generation like GPT-3, image generation like DALL-E 2, audio generation, video generation, and molecule generation for drug discovery. As the field of generative modelling continues to evolve, new applications and use cases are likely to emerge, driving innovation in various industries.
We invite you to submit high-quality papers to this Special Issue, with subjects covering the whole range from theory to applications.
Dr. Sandra Ortega-Martorell
Dr. Ivan Olier-Caparroso
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
