Multi-task Learning for Source Attribution and Field Reconstruction for Methane Monitoring-Reference-Cited by-同舟云学术

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Multi-task Learning for Source Attribution and Field Reconstruction for Methane Monitoring

Published:2022-12-17 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Big Data (Big Data)
language:
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Author:

Daw Arka¹,Yeo Kyongmin²,Karpatne Anuj¹,Klein Levente²

Affiliation:

1. Virginia Tech,Dept. of Computer Science,Blacksburg,United States

2. IBM T.J. Watson Research Center,Yorktown Heights,United States

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10020192/10020156/10020603.pdf?arnumber=10020603

Reference21 articles.

1. Estimating the mean and variance of the target probability distribution

2. A digital twin of earth for the green transition;niederer;Nature Computational Science,2021

3. Possible role of wetlands, permafrost, and methane hydrates in the methane cycle under future climate change: A review

4. S3rp: Self-supervised super-resolution and prediction for advection-diffusion process;wang,2021

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. Detection of methane plumes using Sentinel-2 satellite images and deep neural networks trained on synthetically created label data;2023 IEEE International Conference on Big Data (BigData);2023-12-15

2. Above Ground Carbon Biomass Estimate with Physics-Informed Deep Network;IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium;2023-07-16

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