Abstract: Dynamic graphs arise in various real-world applications, and it is often welcomed to model the dynamics in continuous time domain for its flexibility. This paper aims to design an ...

Abstract: Reconstructing time-varying graph signals (or graph time-series imputation) is a critical problem in machine learning and signal processing with broad applications, ranging from missing data ...

Graph database maker Neo4j Inc. today launched Infinigraph, calling it a significant advancement in distributed graph technology. The company said the architecture allows users to run both operational ...

We recommend you to create a new python environment for MAGNN. You might run this command in your anaconda prompt in order to create a new environment: ...

Scalable, high performance knowledge graph memory system with semantic retrieval, contextual recall, and temporal awareness. Provides any LLM client that supports the model context protocol (e.g., ...