Uncertainty-Aware Feature Learning and Anomaly Detection for Unlabeled Complex Data
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Multidisciplinary Applications".
Deadline for manuscript submissions: 17 August 2026 | Viewed by 970
Editors
Interests: uncertainty artificial intelligence; granular computing; feature selection; anomaly detection; unsupervised learning
Interests: granular computing; uncertain information processing; fuzzy sets; continual learning; machine learning
Interests: feature selection; granular computing; graph learning; information fusion; rough set; uncertainty analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The exponential growth of unlabeled complex data in fields such as the IoT, cybersecurity, and healthcare poses significant challenges to intelligent data analytics. Inherent uncertainty (e.g., noise, ambiguity, and incompleteness) in such data severely degrades the performance of traditional feature learning and anomaly detection methods, which often rely on labeled data or ignore uncertainty quantification.
This Special Issue focuses on advancing uncertainty-aware methodologies for unlabeled complex data. It aims to garner cutting-edge research integrating feature learning, uncertainty modeling, and anomaly detection, with an emphasis on innovative frameworks such as granular computing, self-supervised learning, and unsupervised uncertainty quantification.
We welcome original works on theoretical breakthroughs, algorithm innovations, and practical applications to address the gaps between uncertainty handling, discriminative feature extraction, and robust anomaly identification, thereby promoting interdisciplinary progress in this field.
Dr. Zhong Yuan
Dr. Binbin Sang
Dr. Keyu Liu
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 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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy 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 2600 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.
Keywords
- uncertainty modeling
- uncertain information processing
- feature selection
- anomaly/outlier detection
- granular computing
- rough sets
- fuzzy sets
- entropy
- high-dimensional data
- representation learning
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
