Deep Learning Architecture and Applications (2nd Edition)
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Evolutionary Algorithms and Machine Learning".
Deadline for manuscript submissions: 31 October 2026 | Viewed by 115
Special Issue Editor
Interests: machine learning; structural health monitoring; dimensionality reduction; deep learning
Special Issue Information
Dear Colleagues,
Deep learning continues to transform the foundations of data-driven algorithms, enabling new capabilities in modeling complex systems, extracting knowledge from large-scale data, and supporting intelligent decision-making across domains. Recent advances in architectures such as transformers, diffusion models, graph neural networks, and foundation models are redefining how learning systems generalize, adapt, and operate in real-world environments. At the same time, emerging paradigms—including self-supervised learning, multimodal learning, and trustworthy AI—are shaping the next generation of algorithmic design.
This Special Issue aims to provide a platform for innovative contributions in deep learning algorithms, methodological developments, and impactful applications. We welcome original research addressing theoretical advances, novel frameworks, optimization strategies, and deployment in practical contexts.
Topics of interest include, but are not limited to, the following: supervised and unsupervised learning, reinforcement learning, explainable and trustworthy AI, robustness and generalization, multimodal and foundation models, as well as applications in industry, engineering, health, environmental sciences, and other data-intensive fields.
Submissions that bridge algorithmic innovation with real-world implementation are especially encouraged.
Dr. Jersson Xavier Leon-Medina
Guest Editor
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 250 words) can be sent to the Editorial Office for assessment.
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.
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Keywords
- deep learning architectures
- self-supervised and multimodal learning
- transformers and foundation models
- trustworthy and explainable AI
- reinforcement learning and optimization
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Related Special Issue
- Deep Learning Architecture and Applications in Algorithms (21 articles)
