An all-in-one browser-based platform for developers, marketers, and creators—no logins required, no limits, and ...

MicroCloud Hologram’s approach uses a logarithmic encoding method to reduce the number of qubits needed, representing an N-dimensional feature space using just log (N) qubits. The system forms an ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...

Texture recognition is a fundamental problem in computer vision and pattern recognition. Recent progress leverages feature aggregation into discriminative descriptions based on convolutional neural ...

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 ...

The graph database market, driven by AI, is growing at a rate of almost 25% annually. Graph databases support knowledge graphs, providing visual guidance for AI development. There are multiple ...

Document-level Role Filler Extraction exhibits a wide range of application value in natural language processing, including information retrieval, article summarization and trends analysis of world ...

Abstract: Federated Graph Learning (FGL) demonstrates tremendous potential in distributed graph data analysis and modeling. The rapid growth of graph data and the increasing awareness of privacy ...

Introduction: Accurate recognition of martial arts leg poses is essential for applications in sports analytics, rehabilitation, and human-computer interaction. Traditional pose recognition models, ...

Graph generation is an important task across various fields, including molecular design and social network analysis, due to its ability to model complex relationships and structured data. Despite ...