In this talk, I will give a high-level tutorial on graphs of convex sets, with emphasis on their applications in robotics, control, and, more broadly, decision making. Mathematically, a Graph of ...

LangGraph is a powerful framework by LangChain designed for creating stateful, multi-actor applications with LLMs. It provides the structure and tools needed to build sophisticated AI agents through a ...

This is a repository of the code used for the experimental work in my Bachelor thesis on Approximation Algorithms for Graph Edit Distance (GED). It includes implementations, benchmarking scripts, and ...

If you’re like me, you’ve heard plenty of talk about entity SEO and knowledge graphs over the past year. But when it comes to implementation, it’s not always clear which components are worth the ...

Abstract: In this paper, a Mahalanobis Distance-based Graph Attention Network for graph classification, is proposed. In contrast to traditional Graph Attention Networks, the proposed approach learns ...

ABSTRACT: Let G be a connected graph with vertex set V( G ) . Then the degree resistance distance of G is defined as D R ( G )= ∑ { u,v }⊆V( G ) ( d( u )+d( v ) )R( u,v ) , where d( u ) is the degree ...

The most common manifestation of neurological disorders in children is the occurrence of epileptic seizures. In this study, we propose a multi-branch graph convolutional network (MGCNA) framework with ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

Graph Neural Networks GNNs are advanced tools for graph classification, leveraging neighborhood aggregation to update node representations iteratively. This process captures local and global graph ...