Veröffentlichungen

[N26] R. Nather: Finding Conservation Laws of Large Dynamical Systems with Tasks and Futures: A Case Study in Utilizing Dynamic Data Dependencies. Proc. Asynchronous Many‑Task Systems and Applications (WAMTA), 2026. To appear. Slides

[NF25b] R. Nather, C. Fohry: Integration of a Powerful Future Construct into the Taskflow System. SN Computer Science, 2026.

[MNRS25a] M. A. Mebratie, R. Nather, G. F. von Rudorff, W. M. Seiler: Machine learning conservation laws of dynamical systems. Physical Review E 111.2, 2025.

[NF25a] R. Nather, C. Fohry: Futures in Task Graphs - Extending Taskflow With Dynamic Data Dependencies. Proc. Asynchronous Many‑Task Systems and Applications (WAMTA), 2025.

[NRF24] R. Nather, M. Reitz, C. Fohry: Distributed, Resilient and In-Memory Storage of Key-Value Data for HPC. WIP talk, Supercomputing: International Parallel Data Systems Workshop (PDSW), 2024.

[NF24a] R. Nather, C. Fohry: Futures for dynamic dependencies – Parallelizing the H-LU Factorization. Proc. Workshop on Asynchronous Many‑Task Systems and Applications (WAMTA), 2024. Slides

[MBNT23] A. Moallemy-Oureh, S, Beddar-Wiesing, R. Nather, J. Thomas: Marked Neural Spatio-Temporal Point Process Involving a Dynamic Graph Neural Network. Temporal Graph Learning Workshop (TGL). 2023.