51 citations · 63 across the 4 of their papers we have counts for
6 papers · 1 filter
GLINKX: A Scalable Unified Framework For Homophilous and Heterophilous Graphs
Marios Papachristou, Rishab Goel, Frank Portman +2
In graph learning, there have been two predominant inductive biases regarding graph-inspired architectures: On the one hand, higher-order interactions and message passing work well…
Static Prediction of Runtime Errors by Learning to Execute Programs with External Resource Descriptions
David Bieber, Rishab Goel, Daniel Zheng +2
The execution behavior of a program often depends on external resources, such as program inputs or file contents, and so cannot be run in isolation. Nevertheless, software develope…
Out-of-Sample Representation Learning for Multi-Relational Graphs
Marjan Albooyeh, Rishab Goel, Seyed Mehran Kazemi
Many important problems can be formulated as reasoning in knowledge graphs. Representation learning has proved extremely effective for transductive reasoning, in which one needs to…
Time2Vec: Learning a Vector Representation of Time
Seyed Mehran Kazemi, Rishab Goel, Sepehr Eghbali +7
Time is an important feature in many applications involving events that occur synchronously and/or asynchronously. To effectively consume time information, recent studies have focu…
Diachronic Embedding for Temporal Knowledge Graph Completion
Rishab Goel, Seyed Mehran Kazemi, Marcus Brubaker +1
Knowledge graphs (KGs) typically contain temporal facts indicating relationships among entities at different times. Due to their incompleteness, several approaches have been propos…
Representation Learning for Dynamic Graphs: A Survey
Seyed Mehran Kazemi, Rishab Goel, Kshitij Jain +4
Graphs arise naturally in many real-world applications including social networks, recommender systems, ontologies, biology, and computational finance. Traditionally, machine learni…