k-simplex2vec: a simplicial extension of node2vec

원문 초록

We present a novel method of associating Euclidean features to simplicial complexes, providing a way to use them as input to statistical and machine learning tools. This method extends the node2vec algorithm to simplices of higher dimensions, providing insight into the structure of a simplicial complex, or into the higher-order interactions in a graph.

함께 살펴볼 논문

공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.

arXiv:2210.10048공통 태그 BIG-bench Machine Learning공식 코드 · Papers with Code 등록 2022-10-14

AnalogVNN: A fully modular framework for modeling and optimizing photonic neural networks

arXiv:2208.02400공통 태그 BIG-bench Machine Learning공식 코드 · Papers with Code 등록 2022-08-04

Evolutionary bagging for ensemble learning

arXiv:2208.02645공통 태그 BIG-bench Machine Learning공식 코드 · Papers with Code 등록 2022-08-04

Neural network accelerator for quantum control

arXiv:2208.01769공통 태그 BIG-bench Machine Learning공식 코드 · Papers with Code 등록 2022-08-02

Deep Reinforcement Learning for Multi-Agent Interaction

arXiv:2208.01127공통 태그 BIG-bench Machine Learning공식 코드 · Papers with Code 등록 2022-08-01

Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning

arXiv:2208.01439공통 태그 BIG-bench Machine Learning공식 코드 · Papers with Code 등록 2022-08-01

Unsupervised machine learning framework for discriminating major variants of concern during COVID-19

토론

이 논문과 연결된 포럼 글이 아직 없습니다.

포럼에서 토론 찾기