1 code implementation • 4 Aug 2019 • Sabin Devkota, Reyan Ahmed, Felice De Luca, Katherine E. Isaacs, Stephen Kobourov
Stress, edge crossings, and crossing angles play an important role in the quality and readability of graph drawings.
1 code implementation • 30 Apr 2023 • Reyan Ahmed, Mithun Ghosh, Kwang-Sung Jun, Stephen Kobourov
Graph neural networks are useful for learning problems, as well as for combinatorial and graph problems such as the Subgraph Isomorphism Problem and the Traveling Salesman Problem.
1 code implementation • 17 Nov 2023 • Alvin Chiu, Mithun Ghosh, Reyan Ahmed, Kwang-Sung Jun, Stephen Kobourov, Michael T. Goodrich
Graph neural networks have been successful for machine learning, as well as for combinatorial and graph problems such as the Subgraph Isomorphism Problem and the Traveling Salesman Problem.
no code implementations • 11 Feb 2021 • Reyan Ahmed, Greg Bodwin, Faryad Darabi Sahneh, Keaton Hamm, Stephen Kobourov, Richard Spence
In this paper, we consider a multi-level version of the subsetwise spanner in weighted graphs, where the vertices in $S$ possess varying level, priority, or quality of service (QoS) requirements, and the goal is to compute a nested sequence of spanners with the minimum number of total edges.
Discrete Mathematics
no code implementations • 18 Aug 2021 • Reyan Ahmed, Md Asadullah Turja, Faryad Darabi Sahneh, Mithun Ghosh, Keaton Hamm, Stephen Kobourov
Graph neural networks have been successful in many learning problems and real-world applications.