5 citations · 5 across the 5 of their papers we have counts for
6 papers
Poseidon: A OneGraph Engine
Brad Bebee, Ümit V. Çatalyürek, Olaf Hartig +5
We present the Poseidon engine behind the Neptune Analytics graph database service. Customers interact with Poseidon using the declarative openCypher query language, which enables…
A Scalable and Effective Alternative to Graph Transformers
Kaan Sancak, Zhigang Hua, Jin Fang +5
Graph Neural Networks (GNNs) have shown impressive performance in graph representation learning, but they face challenges in capturing long-range dependencies due to their limited…
SGORP: A Subgradient-based Method for d-Dimensional Rectilinear Partitioning
Muhammed Fatih Balin, Xiaojing An, Abdurrahman Yaşar +1
Partitioning for load balancing is a crucial first step to parallelize any type of computation. In this work, we propose SGORP, a new spatial partitioning method based on Subgradie…
Cooperative Minibatching in Graph Neural Networks
Muhammed Fatih Balin, Dominique LaSalle, Ümit V. Çatalyürek
Training large scale Graph Neural Networks (GNNs) requires significant computational resources, and the process is highly data-intensive. One of the most effective ways to reduce r…
Heuristics for Symmetric Rectilinear Matrix Partitioning
Abdurrahman Yaşar, Ümit V. Çatalyürek
Partitioning sparse matrices and graphs is a common and important problem in many scientific and graph analytics applications. In this work, we are concerned with a spatial partiti…
An Iterative Global Structure-Assisted Labeled Network Aligner
Abdurrahman Yaşar, Ümit V. Çatalyürek
Integrating data from heterogeneous sources is often modeled as merging graphs. Given two or more 'compatible', but not-isomorphic graphs, the first step is to identify a graph ali…