Uncertainty-Aware Artificial Intelligence
A special issue of Computers (ISSN 2073-431X).
Deadline for manuscript submissions: 30 September 2024 | Viewed by 15990
Special Issue Editors
2. Research Fellow, Rural Health Research Institute, Charles Sturt University, Orange, NSW 2800, Australia
Interests: artificial intelligence; uncertainty quantification; imbalanced data
2. Nuclear Plasma and Radiological Engineering, University of Illinois Urbana, Champaign, IL 61801, USA
Interests: digital twin; computation nuclear; uncertainty quantification; explainable AI; robust optimization
Special Issues, Collections and Topics in MDPI journals
Interests: cloud computing; networks and distributed systems; blockchain; deep learning; natural language processing
Interests: artificial/computational Intelligence; autonomy applications in aerospace; cybersecurity; 3D printing command/control and assessment; educational assessment in computing disciplines
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Neural networks have brought eye-catching performance improvements the approaches to many prediction and decision-making problems. Machines can perform a variety of complex tasks that only humans could perform several decades ago. In fact, machines are performing better than humans in various fields. However, neural network models provide poor predictions in many situations. The user of neural networks must develop an understanding of situations where neural networks can potentially provide poor performance. A good knowledge of the causes of uncertainties can potentially assist future researchers to design more robust models. Additionally, current users of the prediction systems would be able to understand the credibility of the prediction.
The purpose of this Special Issue is to explore potential improvements that can lead us toward more stable neural network-based solutions. Potential authors are encouraged to submit new concepts according to the submission guidelines. Editors and reviewers will aim to understand and improve the concepts and provide effective feedback to researchers. The issue can potentially bring technological improvements and an improved understanding of concepts among everyone involved, including readers.
Dr. Hussain Mohammed Dipu Kabir
Dr. Syed Bahauddin Alam
Dr. Subrota Kumar Mondal
Dr. Jeremy Straub
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. Computers 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 1800 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
- robust modeling
- uncertainty-aware artificial intelligence
- explainable artificial intelligence
- probabilistic forecast
