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CW-CNN & CW-AN: Convolutional Networks and Attention Networks for CW-Complexes

Khorana, Rahul

arXiv.org Artificial IntelligenceSep-5-2024

We present a novel framework for learning on CW-complex structured data points. Recent advances have discussed CW-complexes as ideal learning representations for problems in cheminformatics. However, there is a lack of available machine learning methods suitable for learning on CW-complexes. In this paper we develop notions of convolution and attention that are well defined for CW-complexes. These notions enable us to create the first Hodge informed neural network that can receive a CW-complex as input. We illustrate and interpret this framework in the context of supervised prediction.

cw-complex, graph, matrix, (15 more...)

arXiv.org Artificial Intelligence

2408.16686

Country:

North America > United States > California > Alameda County > Berkeley (0.04)
Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)

Genre: Research Report > New Finding (0.46)

Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (1.00)

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