Embedding Signals on Graphs with Unbalanced Diffusion Earth Mover’s Distance-Reference-Cited by-同舟云学术

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Embedding Signals on Graphs with Unbalanced Diffusion Earth Mover’s Distance

Published:2022-05-23 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Tong Alexander¹,Huguet Guillaume²,Shung Dennis³,Natik Amine²,Kuchroo Manik⁴,Lajoie Guillaume²,Wolf Guy²,Krishnaswamy Smita⁴

Affiliation:

1. Yale University,Dept. of Comp. Sci.,New Haven,CT,USA

2. Université de Montréal,Dept. of Math. & Stat.; Mila – Quebec AI Institute,Montreal,QC,Canada

3. Yale University,Dept. of Medicine,New Haven,CT,USA

4. Yale University,Dept. of Genetics,New Haven,CT,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09746556.pdf?arnumber=9746556

Reference28 articles.

1. Optimal Transport improves cell-cell similarity inference in single-cell omics data;huizing;BioRxiv,2021

2. The gene mover’s distance: Single-cell similarity via optimal transport;bellazzi;ArXiv,2021

3. Sinkhorn Distances: Lightspeed Computation of Optimal Transport;cuturi;NeurIPS,2013

4. Wasserstein gan;arjovsky;ICML,2017

5. Improved Training of Wasserstein GANs;gulrajani;NeurIPS,2017

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Optimal transport for single-cell and spatial omics;Nature Reviews Methods Primers;2024-08-14

2. Mapping the gene space at single-cell resolution with gene signal pattern analysis;2023-11-27

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