Modular orchestration, fail-safe design, hybrid memory management, and LLM integration with domain knowledge are essential to agentic systems that reason, act, and adapt at scale.

Abstract: Graph data analysis has been used in various real-world applications to improve services or scientific research, which, however, may expose sensitive personal information. Differential ...

A PyTorch implementation of the DeFoG model for training and sampling discrete graph flows. (Please update to the latest version. Recent fixes have been applied ...

Jyväskylä Summer School at the University of Jyväskylä runs from the 4th to the 15th of August 2025 and includes teaching by FiRST's researchers. Please visit the website of the summer school for more ...

This code was tested with PyTorch 2.0.1, cuda 11.8 and torch_geometrics 2.3.1. Note that ${PROJECT_DIR} refers to this directory. The following section outlines the graph-to-graph transformation ...

Abstract: Recent progress in diffusion generative models have reshaped the paradigm in the field of generation. Inspired by these advancements, the research community has extended the application of ...

1 Department of Life Science and Informatics, Graduate School of Engineering, Maebashi Institute of Technology, Maebashi, Gunma, Japan 2 Department of Life Engineering, Faculty of Engineering, ...

Data-hungry AI applications are fed complex information, and that's where graph databases and knowledge graphs play a crucial role.

Infinigraph is a new distributed graph architecture that allows Neo4j’s database to run operational and analytical workloads ...

Jim Morris, solution engineer, Progress, and Stephen Reed, senior account manager, Progress, joined DBTA's webinar, Building Knowledge Graphs to Power Your AI Initiatives, to examine how knowledge ...