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: This paper addresses the resilient leader-follower consensus problem for discrete-time high-order multi-agent systems with time-varying graphs. A resilient control law is proposed for each ...

IIT Guwahati has released the GATE ECE Syllabus for Electronics and Communication Engineering with the official brochure. Get ...

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 ...

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 ...

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, ...

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...

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