Machine Learning and Quantum Computing
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: closed (30 November 2024) | Viewed by 6804
Special Issue Editor
Interests: categorical duality theory; foundations of mathematics; physics and informatics; artificial intelligence and machine learning; quantum physics and quantum computing
Special Issue Information
Dear Colleagues,
Machine learning and quantum computing are transforming the world. That said, their mathematical foundations still remain unclear despite their engineering success, and fundamental questions remain unanswered. For example, why are specific types of neural networks effective for specific types of data? Transformers and CNNs are often used for text and image data, respectively, but is there any mathematical rationale for doing so? It is broadly agreed that quantum contextuality and non-locality are useful resources for quantum computing. However, what fundamental principle exactly allows us to characterise quantum contextually and non-locality is still debated. Some information–physical and other principles have been proposed, but there has been no clear agreement so far.
The aim of this Special Issue is to shed light on foundational issues in machine learning and quantum computing and explore the space of potential solutions to them. Any papers addressing any foundational aspect of machine learning or quantum computing are more than welcome for the Special Issue. Proposed solutions do not have to be complete solutions as long as they address fundamental questions, and we welcome speculative papers that might contribute to pinning down the truth in the future. We hope that theoretical foundational research helps us better understand their underlying principles and thereby contributes to further innovation in engineering applications as well as scientific understanding.
Dr. Yoshihiro Maruyama
Guest Editor
Manuscript Submission Information
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Keywords
- machine learning
- quantum computing
- category theory
- quantum foundations
- artificial general intelligence
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