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Outputs (3148)

Adaptive Graph Learning from Spatial Information for Surgical Workflow Anticipation (2024)
Journal Article
Zhang, F. X., Deng, J., Lieck, R., & Shum, H. P. (2025). Adaptive Graph Learning from Spatial Information for Surgical Workflow Anticipation. IEEE Transactions on Medical Robotics and Bionics, 7(1), 266-280. https://doi.org/10.1109/TMRB.2024.3517137

Surgical workflow anticipation is the task of predicting the timing of relevant surgical events from live video data, which is critical in Robotic-Assisted Surgery (RAS). Accurate predictions require the use of spatial information to model surgical i... Read More about Adaptive Graph Learning from Spatial Information for Surgical Workflow Anticipation.

Predicting effective quenching of stable pulses in slow-fast excitable media (2024)
Journal Article
Marcotte, C. D. (2024). Predicting effective quenching of stable pulses in slow-fast excitable media. Physical Review E, 110(6), Article 064210. https://doi.org/10.1103/physreve.110.064210

We develop a linear theory for the prediction of excitation wave quenching—the construction of minimal perturbations which return stable excitations to quiescence—for localized pulse solutions in models of excitable media. The theory accounts for an... Read More about Predicting effective quenching of stable pulses in slow-fast excitable media.

Optimal Scheduling in a Quantum Switch: Capacity and Throughput Optimality (2024)
Presentation / Conference Contribution
Bhambay, S., Vasantam, T., & Walton, N. (2025, June). Optimal Scheduling in a Quantum Switch: Capacity and Throughput Optimality. Presented at SIGMETRICS '25: 2025 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, Stony Brook, NY, USA

With a growing number of quantum networks in operation, there is a pressing need for performance analysis of quantum switching technologies. A quantum switch establishes, distributes, and maintains entanglements across a network. In contrast to a cla... Read More about Optimal Scheduling in a Quantum Switch: Capacity and Throughput Optimality.

Block Ciphers in Idealized Models: Automated Proofs and New Security Results (2024)
Presentation / Conference Contribution
Ambrona, M., Farshim, P., & Harasser, P. (2024, October). Block Ciphers in Idealized Models: Automated Proofs and New Security Results. Presented at ACM SIGSAC Conference on Computer and Communications Security 2024, Salt Lake City, USA

We develop and implement AlgoROM, a tool to systematically analyze the security of a wide class of symmetric primitives in idealized models of computation. The schemes that we consider are those that can be expressed over an alphabet consisting of XO... Read More about Block Ciphers in Idealized Models: Automated Proofs and New Security Results.

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.

SIRT2 Inhibition by AGK2 Promotes Perinuclear Cytoskeletal Organisation and Reduces Invasiveness of MDA-MB-231 Triple-Negative Breast Cancer Cells in Confined In Vitro Models (2024)
Journal Article
Jessop, E., Young, N., Garcia-Del-Valle, B., Crusher, J. T., Obara, B., & Karakesisoglou, I. (2024). SIRT2 Inhibition by AGK2 Promotes Perinuclear Cytoskeletal Organisation and Reduces Invasiveness of MDA-MB-231 Triple-Negative Breast Cancer Cells in Confined In Vitro Models. Cells, 13(23), Article 2023. https://doi.org/10.3390/cells13232023

Triple-negative breast cancer (TNBC) is a highly aggressive breast cancer subtype characterised by the absence of targetable hormone receptors and increased metastatic rates. As nuclear softening strongly contributes to TNBC’s enhanced metastatic cap... Read More about SIRT2 Inhibition by AGK2 Promotes Perinuclear Cytoskeletal Organisation and Reduces Invasiveness of MDA-MB-231 Triple-Negative Breast Cancer Cells in Confined In Vitro Models.

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.

Complexity framework for forbidden subgraphs II: Edge subdivision and the "H"-graphs (2024)
Presentation / Conference Contribution
Lozin, V. V., Martin, B., Pandey, S., Paulusma, D., Siggers, M., Smith, S., & van Leeuwen, E. J. (2024, December). Complexity framework for forbidden subgraphs II: Edge subdivision and the "H"-graphs. Presented at ISAAC, ISAAC 2024

For a fixed set H of graphs, a graph G is H-subgraph-free if G does not contain any H ∈ H as a (not necessarily induced) subgraph. A recent framework gives a complete classification on H-subgraph-free graphs (for finite sets H) for problems that are... Read More about Complexity framework for forbidden subgraphs II: Edge subdivision and the "H"-graphs.