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SYCL compute kernels for ExaHyPE (2024)
Presentation / Conference Contribution
Loi, C. M., Bockhorst, H., & Weinzierl, T. (2024, March). SYCL compute kernels for ExaHyPE. Presented at 2024 SIAM Conference on Parallel Processing for Scientific Computing (PP), Baltimore, MD

We discuss three SYCL realisations of a simple Finite Volume scheme over multiple Cartesian patches. The realisation flavours differ in the way how they map the compute steps onto loops and tasks: We compare an implementation that is exclusively usin... Read More about SYCL compute kernels for ExaHyPE.

Interactive Digital Storytelling Navigating the Inherent Currents of the Diasporic Mind (2024)
Presentation / Conference Contribution
Nisi, V., Bala, P., Pessoa, M., James, S., & Nunes, N. (2024, December). Interactive Digital Storytelling Navigating the Inherent Currents of the Diasporic Mind. Presented at International Conference on Interactive Digital Storytelling (ICIDS 2024), Barranquilla, Colombia

Due to a recent increase in conflicts, natural disasters, and economic crises, a growing wave of migrant populations has been searching for asylum in Europe. For this population of asylum seekers, the migration process, like currents and rapids, can... Read More about Interactive Digital Storytelling Navigating the Inherent Currents of the Diasporic Mind.

Payment Scheduling in the Interval Debt Model (2024)
Journal Article
Stewart, I., Kutner, D., Friedetzky, T., Trehan, A., & Mertzios, G. (2025). Payment Scheduling in the Interval Debt Model. Theoretical Computer Science, 1028, Article 115028. https://doi.org/10.1016/j.tcs.2024.115028

The network-based study of financial systems has received considerable attention in recent years but has seldom explicitly incorporated the dynamic aspects of such systems. We consider this problem setting from the temporal point of view and introduc... Read More about Payment Scheduling in the Interval Debt Model.

Maximizing Matching Cuts (2024)
Book Chapter
Le, V. B., Lucke, F., Paulusma, D., & Ries, B. (2024). Maximizing Matching Cuts. In P. M. Pardalos, & O. A. Prokopyev (Eds.), Encyclopedia of Optimization (1-10). Springer Nature. https://doi.org/10.1007/978-3-030-54621-2_898-1

Graph cut problems belong to a well-studied class of classical graph problems related to network connectivity, which is a central concept within theoretical computer science.

Neural-code PIFu: High-fidelity Single Image 3D Human Reconstruction via Neural Code Integration (2024)
Presentation / Conference Contribution
Liu, R., Remagnino, P., & Shum, H. P. (2024, December). Neural-code PIFu: High-fidelity Single Image 3D Human Reconstruction via Neural Code Integration. Presented at 2024 International Conference on Pattern Recognition, Kolkata, India

We introduce neural-code PIFu, a novel implicit function for 3D human reconstruction, leveraging neural codebooks, our approach learns recurrent patterns in the feature space and reuses them to improve current features. Many existing methods predict... Read More about Neural-code PIFu: High-fidelity Single Image 3D Human Reconstruction via Neural Code Integration.

From Category to Scenery: An End-to-End Framework for Multi-Person Human-Object Interaction Recognition in Videos (2024)
Presentation / Conference Contribution
Qiao, T., Li, R., Li, F. W. B., & Shum, H. P. H. (2024, December). From Category to Scenery: An End-to-End Framework for Multi-Person Human-Object Interaction Recognition in Videos. Presented at ICPR 2024: International Conference on Pattern Recognition, Kolkata, India

Video-based Human-Object Interaction (HOI) recognition explores the intricate dynamics between humans and objects, which are essential for a comprehensive understanding of human behavior and intentions. While previous work has made significant stride... Read More about From Category to Scenery: An End-to-End Framework for Multi-Person Human-Object Interaction Recognition in Videos.

Performance of machine learning versus the national early warning score for predicting patient deterioration risk: a single-site study of emergency admissions (2024)
Journal Article
Watson, M., Boulitsakis Logothetis, S., Green, D., Holland, M., Chambers, P., & Al Moubayed, N. (2024). Performance of machine learning versus the national early warning score for predicting patient deterioration risk: a single-site study of emergency admissions. BMJ Health & Care Informatics, 31(1), Article e101088. https://doi.org/10.1136/bmjhci-2024-101088

Objectives: Increasing operational pressures on emergency departments (ED) make it imperative to quickly and accurately identify patients requiring urgent clinical intervention. The widespread adoption of electronic health records (EHR) makes rich fe... Read More about Performance of machine learning versus the national early warning score for predicting patient deterioration risk: a single-site study of emergency admissions.

Intelligent edge–fog interplay for healthcare informatics: A blockchain perspective (2024)
Journal Article
Rathore, N., Gupta, R., Thakkar, N., Gohil, K., Tanwar, S., Aujla, G. S., Alqahtani, F., & Tolba, A. (2024). Intelligent edge–fog interplay for healthcare informatics: A blockchain perspective. Ad Hoc Networks, 169, Article 103727. https://doi.org/10.1016/j.adhoc.2024.103727

This paper explores artificial intelligence (AI) and edge–fog interplay to strengthen healthcare informatics (HCI), while also considering the blockchain perspective for securing HCI to transform cloud-based HCI to edge–fog-based HC... Read More about Intelligent edge–fog interplay for healthcare informatics: A blockchain perspective.

Artificial Intelligence for Geometry-Based Feature Extraction, Analysis and Synthesis in Artistic Images: A Survey (2024)
Journal Article
Vijendran, M., Deng, J., Chen, S., Ho, E. S. L., & Shum, H. P. H. (in press). Artificial Intelligence for Geometry-Based Feature Extraction, Analysis and Synthesis in Artistic Images: A Survey. Artificial Intelligence Review,

Artificial Intelligence significantly enhances the visual art industry by analyzing , identifying and generating digitized artistic images. This review highlights the substantial benefits of integrating geometric data into AI models, addressing chall... Read More about Artificial Intelligence for Geometry-Based Feature Extraction, Analysis and Synthesis in Artistic Images: A Survey.