等变超图扩散神经算子 - CSDN博客
2024年4月23日 · 受超图扩散算法的启发，本工作提出了一种新的HNN架构，命名为ED-HNN，它可以可证地逼近任何连续等变超图扩散算子，可以模拟各种高阶关系。 ED-HNN可以通过将超 …
[2404.01039] A Survey on Hypergraph Neural Networks: An In …
2024年4月1日 · As networks of HOIs are expressed mathematically as hypergraphs, hypergraph neural networks (HNNs) have emerged as a powerful tool for representation learning on …
Discrete Two-Heterogeneous-Neuron HNN and Chaos-Based …
In this article, we propose a simple discrete model of self-connectionless HNN in which two heterogeneous neurons have different activation functions of sine and hyperbolic tangent.
A Survey on Hypergraph Neural Networks: An In-Depth and...
2023年12月31日 · As networks of HOIs are expressed mathematically as hypergraphs, hypergraph neural networks (HNNs) have emerged as a powerful tool for representation …
Hyperbolic Graph Neural Networks at Scale: A Meta Learning …
2023年10月29日 · Abstract: The progress in hyperbolic neural networks (HNNs) research is hindered by their absence of inductive bias mechanisms, which are essential for generalizing …
Clipped Hyperbolic Classifiers Are Super-Hyperbolic Classifiers
Our experiments demonstrate that clipped HNNs become super-hyperbolic classifiers: They are not only consistently better than HNNs which already outperform ENNs on hierarchical data, …
清华大学团队NSR综述：混合神经网络推动类脑计算
2024年3月28日 · 近期，清华大学类脑计算研究中心 赵蓉 教授团队和 施路平 教授团队合作在 《国家科学评论》 （National Science Review, NSR） 发表了 关于混合神经网络 （Hybrid Neural …
[2402.02478] Why are hyperbolic neural networks effective? A …
2024年2月4日 · In this paper, we propose a benchmark for evaluating HRC and conduct a comprehensive analysis of why HNNs are effective through large-scale experiments. Inspired …
National Science Review | 混合神经网络HNN推动类脑计算
2024年2月26日 · 清华大学类脑计算研究中心 赵蓉 教授团队和 施路平 教授团队合作在《国家科学评论》（National Science Review, NSR）发表了 关于混合神经网络（Hybrid Neural …
Training HNNs without backpropagation - Ata's blog
2024年12月1日 · Our recent paper, “Training Hamiltonian neural networks without backpropagation”, introduces an approach that does just that. By leveraging data-driven …
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