Outputs (2)

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.

Computational modeling of interval distributions in tonal space reveals paradigmatic stylistic changes in Western music history (2024)
Journal Article
Moss, F. C., Lieck, R., & Rohrmeier, M. (2024). Computational modeling of interval distributions in tonal space reveals paradigmatic stylistic changes in Western music history. Humanities and Social Sciences Communications, 11(1), Article 684. https://doi.org/10.1057/s41599-024-03168-1

Diachronic stylistic changes in music are to a large extent affected by composers’ different choices, for example regarding the usage of tones, intervals, and harmonies. Analyzing the tonal content of pieces of music and observing them over time is t... Read More about Computational modeling of interval distributions in tonal space reveals paradigmatic stylistic changes in Western music history.