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1
Machine Learning for Science: Mathematics at the Interface of Data-driven and Mechanistic Modelling
11. Jun 2023 - 17. Jun 2026 • Oberwolfach, Deutschland
Veranstalter:
Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)
Eintrags-ID:
1494904
2
Dagstuhl Research Meeting — A long-term strategy for NFDI for DataScience and Artificial Intelligence
28. Okt 2024 - 29. Okt 2024 • Schloss Dagstuhl, Wadern, Deutschland
Veranstalter:
Schloss Dagstuhl - Leibniz-Zentrum für Informatik
Zusammenfassung:
The vision of NFDI4DS is to support all steps of the complex and interdisciplinary research data lifecycle in Data Science and Artificial Intelligence. The overarching objective of NFDI4DS is the development, establishment, and sustainment of a national research data infrastructure for the Data Science and Artificial Intelligence community. The key idea is to work towards increasing the transparency, reproducibility and fairness of Data Science and Artificial Intelligence projects, by making all digital artifacts available, interlinking them, and offering innovative tools and services. Within this Dagstuhl Research Meeting, the NFDI4DS partners will reflect on their progress so far, and will work on their long-term strategy.
Eintrags-ID:
1566284
3
Dagstuhl-Seminar — Graph Algorithms: Distributed Meets Dynamic
17. Nov 2024 - 22. Nov 2024 • Schloss Dagstuhl, Wadern, Deutschland
Veranstalter:
Schloss Dagstuhl - Leibniz-Zentrum für Informatik
Zusammenfassung:
In modern computational systems, the need to handle large-scale inputs imposes interesting computational challenges. Two such challenges are (1) the need to distribute the computation over multiple units, and (2) the dynamic nature of the input, which may undergo changes over time. A particular class of problems studied in these settings is when the input to the computational task is a huge graph. The field of dynamic graph algorithms addresses efficiently processing edge/vertex insertions/deletions in the input graph. In distributed graph algorithms, the input resides across multiple machines, and the goal is to solve the problem while minimizing the number of rounds of communication. Both of these rich research areas have been extensively studied since at least the 1980’s. We know of efficient algorithms for a large variety of tasks, such as shortest paths problems, coloring, subgraph finding, symmetry breaking, approximations, and many more. However, there are still fundamental problems with no known efficient solutions in some of these models, and even more where the exact complexity of computation is yet to be determined. In the recent years, a number of influential works show how transferring ideas from one of these models to the other provides progress on some of the long-lasting open problems. The goal of this Dagstuhl Seminar is to build a bridge between the two research communities of dynamic graph algorithms and distributed computing, by working together on joint research frontiers.
Eintrags-ID:
1589390
4
Data Assimilation: From Mathematical and Statistical Foundations to Applications
23. Feb 2025 - 28. Feb 2025 • Oberwolfach, Deutschland
Themen:
Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)
Eintrags-ID:
1605165
Verwandte Fachgebiete:


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